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Toxicity of urban particulate matter: long-term health risks, influences of surrounding geography, and diurnal variation in chemical composition and the cellular oxidative stress response

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Toxicity of urban particulate matter: long-term health risks, influences of surrounding geography, and diurnal variation in chemical composition and the cellular oxidative stress response

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Content Copyright 2018 Christopher David Lovett

Toxicity of Urban Particulate Matter: Long-Term Health Risks,
Influences of Surrounding Geography, and Diurnal Variation in
Chemical Composition and the Cellular Oxidative Stress Response

by

Christopher David Lovett

A dissertation presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ENVIRONMENTAL ENGINEERING)

December 2018

i

Acknowledgements
This dissertation resulted from the collaborative efforts of several people around the world,
and I am deeply indebted to all of them. Without the contributions and support of each and every
one of my colleagues listed below, along with their academic rigor and commitment to scientific
inquiry, the research described herein would not have been possible.
First and foremost, I would like to thank my Ph.D. advisor, Professor Constantinos Sioutas,
whose constant support, advice, guidance, and encouragement enabled me to work quickly,
efficiently, and rigorously, producing work of the highest quality. From wherever he might be in
the world, Professor Sioutas was always available to provide almost immediate feedback and
suggestions in response to any questions or concerns I might have, whether these were regarding
methodological issues, results analysis or data interpretation, editing, revising, or submitting a
manuscript, or just general advice regarding life, academia, and the future of my career.
Of almost equal importance has been the extensive feedback, guidance and discussion
provided by my unofficial co-advisor, Professor Caleb Finch, along with key members of his
research team, Drs. Todd Morgan and Mafalda Cacciottolo. I deeply appreciate their patience in
guiding me as I explored the biochemical and molecular biological aspects of my research. I am
also grateful to Amin Haghani for his tireless help with many of the cellular assays I performed.
I would also like to thank Professor George Ban-Weiss, who in addition to serving on my
dissertation committee, has also been a great mentor to me. I will always fondly remember the
brief, and regrettably few, discussions we’ve had during my time at USC regarding life, research,
academia, and avant garde music. Thank you.
Thanks also to the additional faculty members who served on my Ph.D. qualifying exam
committee, Professors Kelly Sanders and Felipe De Barros, for providing valuable comments
ii

and feedback regarding my dissertation research as it progressed. Their insightful questions and
novel perspectives on the implications of my research have greatly enriched this dissertation.
My friends and colleagues in the USC Aerosol Lab, past and present, including Mohammad
Sowlat, Amirhosein Mousavi Nasabi Shams, Arian Saffari, Farimah Shirmohammadi, Sina
Taghvaee, and Sina Hasheminassab, have all been a true pleasure to work with. I’ve experienced
great discussions, camaraderie, friendship, encouragement, and inspiration - as well as the
occasional heated argument - during my time with you at USC. This has not only allowed me to
gain a deeper understanding of the intricacies of atmospheric aerosols and particulate matter, but
has also greatly enriched my professional and personal growth as both an engineer and scientific
researcher. Through your shining examples of diligence and intelligence, I have also learned the
true meaning of khafan. I am deeply grateful for our time together and will miss you all.
Without the hard work of several of my collaborators at other institutions around the world,
none of the research detailed in this dissertation would have been possible. Thank you to Dean
Alan Shihadeh, Professor Najat Saliba, Mohamad Baasiri, and Khairallah Atwi, my colleagues at
the American University of Beirut, for help with much of the data and sample collection, as well
as providing feedback and guidance on our resulting research papers. Thanks also to Drs. Martin
Shafer and Jamie Schauer at the Wisconsin State Lab of Hygiene for their extensive and prompt
laboratory analyses and for always being available to provide detailed answers to any and all of
the questions I might have had over the years regarding chemical analysis methodology.
Finally, I’d like to acknowledge the University of Southern California’s Viterbi School of
Engineering for providing financial support during part of my tenure, in the form of the Dean’s
Ph.D. Fellowship. I’m also grateful to the National Institutes of Health for funding much of my
research, in the form of research grants RF1-AG051521-01 and R21-AG050201-01A1.
iii

Table of Contents
Acknowledgements i
List of Figures vi
List of Tables vii
Abstract viii
Chapter 1: Introduction 1
1.1 Background 1
1.2 Research Overview 3
Chapter 2: Diurnal Variation in the Oxidative Stress Response to Primary Traffic
vs. Photochemically Aged Fine Particulate Matter (PM2.5) 8
2.1 Introduction 9
2.2 Methodology 13
2.2.1 Particulate Sample Collection 13
2.2.2 PM Gravimetric Analysis 14
2.2.3 PM Chemical Species Analysis 14
2.2.4 Alveolar Macrophage In Vitro Assay 14
2.2.5 Microglia In Vitro Assays 16
2.3 Results 20
2.3.1 Alveolar Macrophage Assay 20
2.3.2 Microglia Assays 20
2.3.3 Chemical Composition of PM2.5 Slurry Samples 23
2.4 Discussion 25
2.5 Summary and Conclusions 28
Chapter 3: Cancer and Non-Cancer Health Risks to Los Angeles Commuters:
Roadway, Light-Rail, and Subway Transit Routes 30
3.1 Introduction 30
3.2 Methodology 34
3.2.1 Sampling Methods 34
3.2.2 Sampling Locations and Route Descriptions 36
3.2.3 Sample Analysis 39
3.2.4 Cancer and Non-Cancer Risk Calculations 39
iv

3.3 Results and Discussion 43
3.3.1 Particulate Matter Composition at Sampling Sites 43
3.3.2 Cancer and Non-Cancer Health Risks Along Commuter Routes 46
3.4 Summary and Conclusions 51
Chapter 4: Oxidative Potential of Ambient Particulate Matter in Beirut During
Saharan and Arabian Dust Events 52
4.1 Introduction 53
4.2 Methodology 55
4.2.1 Sampling Location and Schedule 55
4.2.2 Gravimetric and Chemical Analyses 57
4.2.3 Determination of PM Oxidative Potential via the Alveolar
Macrophage (AM) Assay 58
4.2.4 Correlational Analysis of Oxidative Potential and PM Species 59
4.3 Results and Discussion 59
4.3.1 Mass Concentration and Chemical Composition of PM 59
4.3.2 PM Oxidative Potential 65
4.3.3 Bivariate Correlations Between Individual Species and Oxidative
Potential 68
4.4 Summary and Conclusions 70
Chapter 5: Conclusions 72
Bibliography 74
Appendix A: Oxidative Potential of Primary (POA) and Secondary (SOA) Organic
Aerosols Derived from α-Pinene and Gasoline Engine Exhaust Precursors 97
A.1 Introduction 98
A.2 Methodology 103
A.2.1 Overview 103
A.2.2 POA and SOA Generation 103
A.2.3 α-Pinene Aerosol Sampling Methods 104
A.2.4 Gasoline Engine Exhaust Sampling Methods 105
A.2.5 Particle Sizing 106
A.2.6 Filter Conditioning 106
A.2.7 Laboratory Analyses 106
A.3 Results and Discussion 107
A.3.1 Particle Size Distributions 108
A.3.2 Elemental/Organic Carbon (EC/OC) 109
v

A.3.3 Water-Soluble Organic Carbon (WSOC) 110
A.3.4 Total Metals and Trace Elements 111
A.3.5 Organic Compounds - PAHs, Hopanes, Steranes, Carboxylic Acids 112
A.3.6 Oxidative Potential 115
A.4 Summary and Conclusions 119

vi

List of Figures
Figure 2.1: Oxidative potential of PM 2.5 slurries by alveolar macrophage (DCFH) assay 20
Figure 2.2: Nitric oxide (NO) induction by microglia 22
Figure 2.3: Inflammatory gene mRNA induction in microglia 23
Figure 2.4: Chemical analyses 24
Figure 3.1: Los Angeles commuter routes 36
Figure 3.2a: Excess lifetime cancer risk for metals and diesel exhaust particulate (DEP) 47
Figure 3.2b: Excess lifetime cancer risk for polycyclic aromatic hydrocarbons (PAHs) 47
Figure 3.3: Non-cancer risk (hazard quotient) 48
Figure 3.4a: Excess lifetime cancer risk - totals by site 49
Figure 3.4b: Non-cancer risk (hazard quotient) - totals by site 50
Figure 4.1a: Mass concentrations (μg/m
3
) - dust vs. non-dust days, coarse PM 60
Figure 4.1b: Mass concentrations (μg/m
3
) - dust vs. non-dust days, fine PM 60
Figure 4.2a: Mass concentrations (μg/m
3
) of inorganic secondary ions - dust vs. non-dust days,
coarse PM 61
Figure 4.2b: Mass concentrations (μg/m
3
) of inorganic secondary ions - dust vs. non-dust days,
fine PM 61
Figure 4.3a: Mass concentrations (μg/m
3
) of carbonaceous species - dust vs. non-dust days,
coarse PM 62
Figure 4.3b: Mass concentrations (μg/m
3
) of carbonaceous species - dust vs. non-dust days,
fine PM 63
Figure 4.4a: PM Oxidative potential (μg-Zym/m
3
) - dust vs. non-dust days, coarse PM 66
Figure 4.4b: PM Oxidative potential (μg-Zym/m
3
) - dust vs. non-dust days, fine PM 66
Figure A.1: Biogenic PM (α-pinene) sampling setup 105
Figure A.2: Anthropogenic PM (gasoline engine exhaust) sampling setup 105
Figure A.3: Particle size distribution - engine SOA and α-pinene SOA 108
vii

Figure A.4a: Pre- and post-sampling particle size number distribution - engine POA 109
Figure A.4b: Pre- and post-sampling particle size number distribution - α-pinene SOA 109
Figure A.5: Mass fractions of EC and OC in engine POA & SOA and α-pinene SOA 110
Figure A.6: Mass fractions of WSOC in engine SOA and α-pinene SOA 111
Figure A.7: Concentrations of total metals and trace elements in engine SOA and POA 112
Figure A.8: Cumulative mass fractions of all PAHs - engine SOA and α-pinene SOA 113
Figure A.9: Cumulative mass fractions of hopanes & steranes - engine SOA and α-pinene SOA 113
Figure A.10: Cumulative mass fractions of organic acids C 15-C 30 - engine SOA & α-pinene SOA 114
Figure A.11: Cumulative mass fractions of organic acids - engine SOA and α-pinene SOA 115
Figure A.12: Oxidative potential (mass fractions) - engine SOA & POA and α-pinene SOA 116

List of Tables
Table 3.1: General characteristics of the investigated sampling routes 37
Table 3.2: Cancer Potency (CP), Reference Concentration (RfC) and Reference Exposure Level
(REL) for selected PAHs and metals 41
Table 3.3: Summary statistics of the concentrations (ng/m
3
) of chemical components (metals,
PAHs, & EC) measured in each sampling campaign 45
Table 4.1: Sampling dates following dust episodes 57
Table 4.2: Coarse and fine PM metals content during dust and non-dust episodes 64
Table 4.3: Spearman’s Rho correlation coefficients 69

viii

Abstract
Particulate matter (PM) is perhaps the most ubiquitous form of air pollution affecting
urban populations in the world today. With the adverse health outcomes and accompanying
deaths due to PM exposures on the rise every year, the need to better understand PM, its toxicity,
and possible mitigation strategies has never been more urgent, especially in large urban centers
such as Los Angeles, California. Much of the research in this dissertation examines one common
measure of PM toxicity, cellular oxidative stress, which has been linked to several health
problems, ranging from cardiovascular disease and respiratory distress to neurodegenerative
disorders such as Alzheimer’s and Parkinson’s diseases. Various factors that may reduce or
exacerbate this toxicity, including photochemical oxidation and regional geographic and
meteorological influences are also examined. Additionally, the long-term health risks, such as
cancer and non-cancerous organ and tissue damage, posed to Los Angeles commuters facing
daily exposures to airborne particulate matter are calculated based on measurements of PM
composition and concentration made along the most common commuter routes.
The research findings presented in this dissertation provide further evidence that PM
composition and its health effects mediated by oxidative stress are highly complex and
susceptible to the influence of several factors, including geographical context, specific source
domains, and time of day. While secondary PM that has undergone photochemical oxidation
reactions generally has been found to induce a larger proinflammatory response than freshly
emitted primary PM, this effect is highly dependent on the dominant species present in PM at
any given time and location, and sometimes the reverse may be true. For example, primary motor
vehicle emissions, which are dominant in the urban atmosphere near freeways, contain large
amounts of redox-active transition metals such as copper and nickel, as well as water-insoluble
ix

organic compounds such as polycyclic aromatic hydrocarbons (PAHs). Based on the research
findings presented herein, these species actually result in greater oxidative stress than secondary
PM. While some of these findings may seem counter-intuitive considering previous research, the
use of a more precise sampling methodology, namely the direct aerosol-into-liquid collection
system, has made it possible to capture PM samples more representative of actual PM exposures
urban residents experience.
The research findings presented in this dissertation are an integral component of the ongoing
accumulation of knowledge and understanding of urban PM and its health effects. As more data
from long-term epidemiological studies and other sources become available in the future, a more
complete picture will undoubtedly continue to develop. This dynamic process of discovery and
comprehension is vital for regulatory efforts to continue evolving, becoming ever more refined,
efficient, and effective, allowing for cleaner air and the improved health of urban residents
around the world.

1
Chapter 1

Introduction
1.1 Background
Urban air pollution has profoundly affected human health throughout much of the twentieth
and twenty-first centuries as ever-burgeoning modern society has become increasingly more
industrialized, and is directly responsible for morbidity and mortality in a multitude of exposed
individuals worldwide. According to 2012 data obtained from the World Health Organization
(WHO), 11.6 % of all premature deaths (approximately 6.5 million) in both developed and
developing countries that year were linked to air pollution. 3 million of these deaths were
attributable solely to ambient (outdoor) air pollution exposures, which resulted in complications
related to airborne toxins such as ischemic heart disease, chronic obstructive pulmonary disease
(COPD), and stroke (WHO, 2016). The lethal effects of air pollution have become even more
widespread in recent years. According to a 2017 report in the Lancet, complications related to
environmental pollution were responsible for approximately 9 million deaths in 2015, which is,
as the authors emphasize, “three times more deaths than from AIDS, tuberculosis, and malaria
combined, and 15 times more than from all wars and other forms of violence.” Of these 9 million
deaths, 6.5 million were attributable to air pollution (Landrigan et al., 2017). Thus, it is no
surprise that, prompted in part by the high frequency of extreme air pollution events worldwide,
as well as the significant baseline air quality problems that plague many developed and
developing countries, including the United States, China, India, and Mexico, an increasing
amount of scientific research has been focused on atmospheric pollution, specifically airborne
particulate matter (PM), and its devastating health effects.
2

The complicated intrinsic composition and various source profiles of PM as compared to
other airborne pollutants, as well as its ability to effectively penetrate the lungs, circulatory
system and central nervous system, while often carrying with it significant quantities of toxic
chemicals that have adsorbed onto its surface, makes PM a particularly pernicious form of air
pollution thought to be responsible for most of the observed debilitating health impacts resulting
from exposure to airborne pollutants. Epidemiological studies, as well as in vivo and in vitro
experiments, have linked airborne particulate matter, especially fine PM (i.e. PM < 2.5 µm in
diameter, or PM2.5), which can penetrate deep into the lungs and easily enter the bloodstream, to
several health problems including respiratory distress, asthma, lung cancer, stroke, coronary
heart disease, and heart failure (Dockery et al., 1993; Shah et al., 2013; Kim et al., 2013; Delfino
et al., 2005; Samet et al., 2000; Dominici et al., 2006), as well as central nervous system (CNS)
oxidative stress and neuroinflammation, which may lead to subsequent neural degeneration,
Alzheimer’s disease, and other dementias (Davis et al., 2013; Levesque et al., 2011; Cheng et al.,
2016a, 2016b; MohanKumar et al., 2008).
Emissions of airborne particulate matter in the greater Los Angeles area are of particular
concern due to its large population density, mixed residential and industrial zoning, and dense
vehicular traffic along the main arteries of the city, all set within a Southern California climate
that affords several hours of sunlight each day for much of the year that facilitates the
transformation of freshly emitted PM into potentially more toxic secondary products. The urban
atmosphere over Los Angeles is replete with products of fossil-fuel combustion continuously
supplied by the high volume of daily freeway traffic, along with industrial emissions emanating
from nearby processing, manufacturing, oil-refining, and power-generation facilities. Arguably,
the bulk of these pollutants are emitted in the form of particulate matter, which does not exist as
3

a static, homogenous pollutant, but rather undergoes physicochemical change throughout the day
via oxidation reactions catalyzed by the abundant ultraviolet in which the city basks, ultimately
leading not only to deleterious health effects, but also reduced visibility. Further research into the
specific toxicity mechanisms, transport properties, and biological fate of particulate matter is
vital to our increased understanding of its effects, as well as our ability to devise successful
strategies to prevent or mitigate its damage. The research discussed and proposed herein explores
not only the health effects and risks commonly associated with PM exposures in Los Angeles, on
both the macroscopic scale of health risk assessment and the microscopic scale of in vitro assays
to quantify cellular oxidative stress and inflammation, but also examines the physicochemical
changes in PM that occur due to interactions with UV light, and how these changes in PM
composition may result in differential cellular responses to particulate exposures.
1.2 Research Overview
We begin by presenting an experiment in which in vitro assays were used to examine cellular
oxidative stress and inflammation in response to both primary and secondary PM collected in
central Los Angeles. Differences between the composition and oxidative potential of primary
PM deriving from fresh traffic emissions, and that of secondary PM, consisting largely of
photochemical oxidation products, were examined. Additional in vitro assays were also done to
investigate the cellular production of nitric oxide (NO) and various proinflammatory biomarkers
in response to each type of PM exposure. Aqueous slurry samples of fine particulate matter
(PM2.5) were obtained using a direct aerosol-into-liquid collection system at a central Los
Angeles site adjacent to the I-110 freeway. Sample slurries consisted of primary, traffic-derived
PM collected from 6-9am (morning), and secondary, photochemically aged PM collected from
12-4pm (afternoon). These aqueous PM slurries were characterized by chemical analyses, as well
4

as in vitro assays utilizing NR8383 (alveolar macrophage) and BV-2 (microglia) murine cell
lines. Previous studies had shown that secondary PM contains a higher fraction of oxidized PM
species, therefore we hypothesized that photochemically-aged PM slurry samples would induce a
greater inflammatory response, as compared to primary PM. Contrary to expectations, primary,
traffic-derived PM elicited a greater NO response, as well as a greater upregulation of several
genes coding for various proinflammatory chemokines and cytokines, including interleukins 1β
and 6 (IL-1β, IL-6) and the monocyte chemoattractant protein 1 (MCP-1, aka CCL2), than
secondary PM samples. These results were complemented by results of the alveolar macrophage
assay for PM oxidative potential, which revealed a greater production of intracellular redox
active species in response to primary as compared to secondary particulate matter. This effect is
believed to be driven largely by the greater transition metal and water-insoluble organic carbon
(WIOC) content of primary PM, which are two components known to increase the toxicity of
particulate matter.
In a second study, we examined the cancer and non-cancer health risks associated with PM
exposures that commuters are subjected to while traveling along various routes in Los Angeles.
Workers within the megacity of Los Angeles are exposed to significant amounts of airborne
particulate matter during their daily commutes, which often exceed 30-60 minutes each way.
Chemical species present in roadway and railway PM, including benzo(a)pyrene (BaP) and
hexavalent chromium (Cr
6+
), present substantial cancer and non-cancer health risks. To examine
these health risks, PM samples were collected and quantitatively speciated along five major
commuter routes, including the METRO red line (subway) and gold line (light rail), the I-110
and I-710 freeways, and high-density surface streets (Sunset and Wilshire Boulevards). Using the
collected PM species concentration data, along with cancer potency (CP) and Reference Dosage
5

(RfD) factors obtained from the United States Environmental Protection Agency (USEPA) and
California's Office of Environmental Health Hazard Assessment (OEHHA), cancer and non-
cancer health risks were calculated. In contrast to previous research indicating that polycyclic
aromatic hydrocarbon (PAH) components of Los Angeles roadway PM (e.g. along the I-710
freeway) lead to the greatest cancer risk, the current analysis revealed that exposure to
carcinogenic transition metals, particularly hexavalent chromium, which are especially prevalent
along the underground METRO red line route, results in the greatest cancer and non-cancer
health risks. Based on these data, it was concluded that the best option for commuters is to use
above-ground light-rail transportation (e.g. the METRO gold line), which allows for greater
ventilation and reduced exposure to both traffic-generated PAHs and railway-related metals.
A third study examines the influence of desert dust events on the air quality of Beirut,
Lebanon, a large urban city in the Middle East with a climate similar to that of Los Angeles. In
this study, we measured changes in the oxidative potential of airborne PM in Beirut collected
during dust events originating in the Sahara and Arabian deserts, relative to the oxidative
potential of PM collected during non-dust days, and determined specific correlations between
various PM species and redox activity in both conditions. Segregated fine and coarse PM
samples collected by our collaborators at the American University of Beirut (AUB), during dust
events as well as during non-dust periods, were analyzed for chemical composition. To measure
the oxidative potential of these samples, and determine whether the PM redox activity was
affected by dust events, the in vitro alveolar macrophage dichlorodihydrofluorescein (DCFH)
assay was performed. Additionally, a bivariate correlational analysis of specific PM components
and oxidative potential data was performed to calculate Spearman’s rho coefficients, which
revealed the relationship between specific PM species and oxidative potential during both dust
6

events and non-dust days. We found that the oxidative potential of PM was higher during non-
dust days, and that, in both conditions, the measured oxidative potential was highly correlated
with tracers of vehicular tailpipe and non-tailpipe emissions, as well as secondary organic
aerosols (SOA), including water-soluble organic carbon (WSOC). Thus, while the oxidative
potential of urban PM in Beirut was mostly the result of vehicle emissions and SOA, the
contribution of desert dust aerosols, composed mostly of crustal elements such as Mg, Ca, and
Ba, did not increase this redox activity. These results are of great value to all countries of the
Middle East in understanding the potential health effects of periodic dust storms arising in the
Arabian and Sahara deserts.
A fourth study, included in Appendix A, examines the chemical characteristics of two types
of airborne particulate matter, primary and secondary PM, of both anthropogenic and biogenic
origin. This reaction chamber study, performed in collaboration with researchers at the American
University of Beirut (AUB), was conducted to determine the properties of both anthropogenic
and biogenic primary organic aerosols (POA), as well as their photochemically oxidized
secondary organic aerosol (SOA) products formed during exposure to ultraviolet light.
Specifically, we compared the chemical composition (elemental and organic carbon (EC/OC),
metals, water soluble OC (WSOC), organic species), particle size distributions, and oxidative
stress potentials (assessed by means of the alveolar macrophage assay) of aerosols from raw and
oxidized gasoline engine exhaust (anthropogenic), and pure and oxidized α-pinene (biogenic).
Comparisons of oxidative potential between the various aerosol systems were made on a per-unit
particle mass basis.
This study is included only as an Appendix due to various methodological flaws and
potential sources of error revealed during the peer-review process. We are currently in the
7

process of refining and repeating this study with our AUB colleagues, and thus it is not included
in the main body of the dissertation. Our preliminary findings, however, indicate that
anthropogenic SOA (photo-oxidized gasoline engine exhaust) produce the greatest oxidative
response compared to biogenic (α-pinene) SOA, indicating that anthropogenic emissions may be
the most harmful. However, we must also take into consideration spatial and temporal
differences in the composition of both biogenic and anthropogenic SOA, as well as the local
concentrations of various species making significant contributions to the oxidative potential of
ambient PM, which may vary widely depending on the given region and time of year.
Collectively, the four studies presented in this dissertation provide us with critical data for
use in further characterizing the differences between primary and secondary PM, of both
biogenic and anthropogenic origin, as well as the ensuing oxidative stress response of cells
exposed to these various types of particulate matter. Additionally, the calculated health risks
faced by workers commuting in Los Angeles are presented, and add insights into the
consequences of long-term PM exposures along commonly used travel routes. Finally, our
findings of the effects of a naturally occurring environmental phenomenon (i.e. dust events) on
PM composition and oxidative potential adds another layer of complexity to our overall
understanding of airborne PM as it exists in the urban atmospheres of large cities that may be
affected by the geographical surroundings in which they are embedded.

8

Chapter 2

Diurnal Variation in the Oxidative Stress Response to Primary Traffic vs.
Photochemically Aged Fine Particulate Matter (PM2.5)

Ambient particulate matter (PM) smaller than 2.5 µm in diameter (PM2.5) has strong
epidemiological associations with several adverse health outcomes as well as the risk of
dementia and accelerated cognitive decline during aging. This study examined diurnal variations
in proinflammatory responses to PM2.5 as its composition and oxidative potential change over the
course of the day due to photochemical oxidation reactions catalyzed by ultraviolet (UV) light.
Time-integrated aqueous slurry samples of ambient PM2.5 were obtained using a direct aerosol-
into-liquid collection system at a central Los Angeles site. Ambient PM2.5 samples consisting of
fresh traffic emissions, largely composed of primary PM, were collected from 6-9am in the
morning (am-PM2.5). PM2.5 samples were also collected in the afternoon from 12-4pm (pm-
PM2.5), when PM composition is dominated by products of photochemical oxidation (secondary
PM). The diurnally phased PM2.5 slurries were characterized for chemical composition, followed
by in vitro assays, using NR8383 (alveolar macrophage) and BV-2 (microglia) cell lines, to
assess induced oxidative stress. Because secondary PM contains a higher fraction of oxidized
PM species, we hypothesized that the pm-PM2.5 slurry would induce a greater inflammatory
response than primary am-PM2.5, as has previously been demonstrated. Contrary to expectations,
the am-PM2.5 slurry elicited a greater production of proinflammatory cytokines IL-1β, IL-6, and
CCL2 (MCP-1), and generated more of the cell-signaling free radical nitric oxide (NO), than the
pm-PM2.5 slurry. These findings were complemented by results of the alveolar macrophage
dichlorodihydrofluorescein (DCFH) assay, which revealed greater oxidative stress in cells
exposed to am-PM2.5. The observed effects may be in part attributed to the greater transition
metal and water-insoluble organic carbon (WIOC) content of am-PM2.5 (primary PM) compared
to pm-PM2.5 (secondary PM), as these two classes of compounds can increase PM2.5 toxicity.
This chapter is based on the following publication:
Lovett, C., Cacciottolo, M., Shirmohammadi, F., Haghani, A., Morgan, T. E., Sioutas, C., & Finch, C. E.
(2018). Diurnal variation in the toxicity of urban fine particulate matter (PM 2.5) as determined by in
vitro assays of acute oxidative stress. F1000 Research, 7, 596. DOI: 10.12688/f1000research.14836.2

9

2.1 Introduction
Compared to other gaseous airborne pollutants, the complicated intrinsic composition and
source profile of particulate matter (PM), which often includes significant quantities of toxic
chemicals adsorbed onto the surface of its carbon core, as well as its ability to effectively
penetrate the lungs, circulatory system, and central nervous system, makes particulate matter an
especially pernicious form of air pollution that is responsible for several of the most serious
health impacts associated with air pollution. Thus, further research into the specific composition,
toxicity mechanisms, transport properties, and biological fate of various forms of particulate
matter is vital to our increased understanding of its properties and effects, as well as our ability to
devise successful strategies for preventing or mitigating its damage.
Particulate matter with an aerodynamic diameter less than 2.5 µm, known as fine PM or
PM2.5, is especially problematic as it penetrates deep into the lungs and has been associated with
diverse health problems and chronic diseases, including asthma, chronic obstructive pulmonary
disease (COPD), lung cancer, and coronary heart disease (Delfino et al., 2005, 2011; Shah et al.,
2013; Kim et al., 2013; Samet et al., 2000; Dominici et al., 2006; Dockery et al., 1993). Many of
these adverse health effects experienced as a consequence of PM2.5 and UFPM exposures are
mediated by the body’s defensive cellular response to noxious stimuli, the oxidative stress
response, which includes the generation of intra- and extracellular oxidizing species that are
often collectively referred to as reactive oxygen species (ROS) and is prompted by several
proinflammatory pathways. Oxidative stress is thus strongly correlated with ROS formation, and
assays to measure ROS activity, such as the alveolar macrophage dichlorodihydrofluorescein
(DCFH) assay, are commonly used as a reliable metric of the proinflammatory response.
10

Consisting of reactive forms of O2, including short-lived hydroxyl and oxygen radicals (HO·
and O2·) as well as other oxygen compounds such as hydrogen peroxide (H2O2) and the
superoxide ion (O2
-
), reactive oxygen species are generated as part of an attack on foreign
biological contaminants, causing direct damage to the DNA, lipids and proteins of invading
microbes or fungi. Upregulation of various chemokines and cytokines (e.g. interleukins 6 and 8
(IL-6, IL-8) and tumor necrosis factor alpha (TNFα)) is part of the general cellular inflammatory
response. The oxidative stress response is also a common component of innate immune defense
mechanisms associated with activation of the antioxidant regulatory protein Nrf-2 (NF-E2-
related factor 2), as well as TLR-4 (toll-like receptor 4), which induces production of several
proinflammatory cytokines (Zhang et al., 2012; Woodward et al., 2017a; Li et al., 2003b, 2009a).
While optimized to defend against living contaminants, these inflammatory cascades can also
be triggered by extracellular debris and other physical contaminants, including of particulate
matter with its many heterogeneous and complex chemical components. Recent epidemiological
studies have also linked chronic fine and ultrafine (UFPM, Dp < 0.20 µm) PM exposures to
Alzheimer’s disease and accelerated cognitive decline (Cacciottolo et al., 2017; Chen et al.,
2015; Chen et al., 2017). Correspondingly, rodent models have also shown robust indicators of
inflammation and oxidative stress to PM2.5 fractions in the brain, arteries, and lungs (Morgan et
al., 2011; Zhang et al., 2012; Li et al., 2003a; Davis et al., 2013; Levesque et al., 2011; Cheng et
al., 2016a, 2016b; MohanKumar et al., 2008).
In addition to the epidemiological associations with chronic disease, we must also consider
diurnal variations in airborne particulate matter chemistry that are not included in most long-term
epidemiological studies. Ambient air pollution toxicity changes over the course of a day, as is
suggested by diurnal variations in emergency department admissions for dementia (Linares et al.,
11

2017), ischemic stroke (Han et al., 2016), and respiratory conditions (Darrow et al., 2011).
Although these admissions were more strongly associated with ozone than with PM2.5 in all three
of these studies, diurnal changes in PM2.5 chemistry must also be considered as an influencing
factor.
As the data in these studies indicate, the health effects resulting from PM2.5 induced oxidative
stress are complicated by substantial changes in its compositional profile, which occur as freshly
emitted primary particles undergo photochemical oxidation reactions over the course of the day,
catalyzed by solar ultraviolet (UV) radiation, resulting in the formation of several intermediary
semi-volatile and volatile organic species (Forstner et al., 1997; Grosjean & Seinfeld, 1989). The
atmospheric aging process yields a varied mixture of oxidation products, including metal oxides,
organic acids, semi-volatile aromatic compounds, and other oxidized organic species that can
self-nucleate or coalesce around core particulate nuclei made up of elemental carbon, metals, and
various other elements. This secondary PM2.5, consisting of coagulated smaller particles and
larger agglomerations of photochemical oxidation products, is known as accumulation mode
particulate matter (Odum et al., 1997; Seinfeld & Pandis, 2016).
Prior studies in the greater Los Angeles conducted to examine compositional changes in PM
due to photo-oxidation and the resulting changes in the cellular oxidative stress response have
provided inconsistent results. Verma et al. (2009) examined quasi-ultrafine particulate matter
(PM0.20) obtained from aqueous extracts of filters collected at a single site in central Los
Angeles. Based on the acellular dithiothreitol (DTT) assay of oxidative stress, all three of the
samples collected in the afternoon, between 11am-2pm, had higher oxidative activity than
samples collected in the morning hours (6-9am), while results of the alveolar macrophage
(DCFH) assay indicated that only two of the three afternoon PM0.20 samples had higher activity.
12

In a subsequent study by Saffari et al. (2015), filterable PM0.25 samples were collected at the
same central Los Angeles sampling site, as well as additional coastal and inland sites, and
aqueous filter extracts were analyzed for composition and oxidative potential. PM0.25 collected at
the coastal Los Angeles site between 6-10am exhibited higher oxidative potential, as measured
by the DCFH assay, than afternoon samples collected from 2-6pm in Upland, CA, the inland site
chosen for its location downwind of the other sites, thus ensuring an enrichment of photo-
oxidized (secondary) aerosol products.
The current study further examines diurnal variations in composition and oxidative potential
of PM samples collected at the central Los Angeles site used in both Verma et al. (2009) and
Saffari et al. (2015). However, to minimize issues in aqueous extracts of filter-collected PM, we
utilized a direct aerosol-into-liquid sampling method to collect time-integrated PM2.5 aqueous
slurries. Additionally, three different in vitro assays were used to measure both direct and
indirect inflammatory responses to PM2.5 exposures. These assays included the alveolar
macrophage (DCFH) assay of oxidative potential, as well as two additional assays utilizing a
microglia cell line (BV-2) to directly examine biomarkers associated with neuroinflammation.
The microglia assays allow us to quantify the induction of the chemical messenger nitric oxide
(NO) due to acute oxidative stress, as well as production of proinflammatory cytokines,
including interleukins 6 and 1β (IL-6 & IL-1β), and monocyte chemoattractant protein 1 (MCP-
1), also known as chemokine (C-C motif) ligand 2 (CCL2). We hypothesized that PM2.5
collected in the afternoon (pm-PM2.5), with its high proportion of secondary photochemical
oxidation products, would result in more oxidative stress and induce a greater proinflammatory
response than its primary PM precursors collected during morning hours (am-PM2.5), consistent
with the findings of Verma et al. (2009).
13

2.2 Methodology
2.2.1 Particulate Sample Collection
All sampling was done at the University of Southern California Particle Instrumentation Unit
(PIU), an air pollution sampling laboratory located approximately 150 meters downwind (east)
of the Los Angeles I-110 freeway (34°1’9” N, 118°16’38” W). PM2.5 samples were collected
weekdays during the morning rush hour period of 6am-9am, as well as during the afternoon
hours of 12pm-4pm, when photochemical products of primary PM oxidation are dominant in the
atmosphere. The sampling campaign was conducted during the summer months of August and
September 2016, ensuring maximum UV sunlight exposure to enhance photochemical oxidation
reactions.
Particulate samples were obtained using a novel high-volume aerosol-into-liquid collection
system, developed and built at USC’s Sioutas Aerosol Laboratory, which provides concentrated
aqueous slurries of fine and/or ultrafine PM (Wang et al., 2013a). A 2.5 µm cut-point slit
impactor at the inlet to the online sampling system removed PM larger than 2.5 µm in diameter
and ensured that only PM2.5 was captured in the aerosol-into-liquid collector. The system was
operated 200 liters per minute (lpm) flow, with two inlet streams, each at 100 lpm flow. The two
inlet aerosol streams merged and passed through a steam bath where ultrapure water vapor
condensed on the surfaces of airborne particles, growing the droplets to 2-3 μm in diameter.
Downstream of the hot water bath, particles entered an electronic chiller, where they were cooled
and condensed, passing through an impactor and accumulating in the aerosol-into-liquid
collector as an aqueous PM2.5 slurry. For each sampling condition, morning and afternoon, one
time-integrated slurry sample was collected for chemical speciation and biological assays.

14

2.2.2 PM Gravimetric Analysis
To determine mass loadings of the PM2.5 slurry samples, a 47 mm Zefluor filter (Pall Life
Sciences, Ann Arbor, MI, USA) was used in each experimental condition to capture PM2.5
passing through a parallel airstream at a flow rate of 9 lpm. Mass of the PM2.5 filter samples was
determined gravimetrically by pre- and post-weighing the Zefluor filters, equilibrated under
controlled temperature (22-24 °C) and relative humidity (of 40-50%) conditions, using a
microbalance (Mettler Toledo Inc., Columbus, OH, USA)
2.2.3 PM Chemical Species Analysis
Aqueous PM2.5 slurry samples were analyzed for various chemical species, including metals
and trace elements, total carbon (TC), and inorganic ions. Total metals and trace elements were
quantified using magnetic-sectored Inductively Coupled Plasma Mass Spectroscopy (SF-ICPMS)
following acid extraction, while analysis of the samples for inorganic anions was achieved by ion
chromatography (IC) (Zhang et al., 2008). Slurry samples were also analyzed for total carbon
concentration using a Sievers 900 Total Carbon Analyzer (Sullivan et al., 2004). All analyses
were performed on one aliquot of each slurry, morning (am-PM2.5) and afternoon (pm-PM2.5).
Measurement uncertainty values were reported in the laboratory results and represent
contributions of analytical error (standard deviation of triplicate analyses) and blank subtraction
(standard deviation of at least three method blanks). Each uncertainty value is calculated as the
square root of the sum of squares of these uncertainty components.
2.2.4 Alveolar Macrophage In Vitro Assay
The dichlorodihydrofluorescein (DCFH) fluorogenic in vitro assay using rat alveolar
macrophages is a widely used index of PM oxidative stress (Rosenkranz, 1992; Landreman et al.,
2008; Shafer et al., 2010). DCFH is sensitive to oxidation by intracellular reactive oxygen
15

species (ROS) as well as other soluble oxidative species present in the cytosol, including
hydroxyl (HO·) and nitric oxide (NO·) free radicals (Schoonen et al., 2006), hydrogen peroxide
(H2O2), transition metals (Ciapetti et al., 1998; Prahalad et al., 1999), and organic compounds
such as quinones (Squadrito et al., 2001; Cho et al., 2005; Forman and Finch, 2018). The
fluorescent product that forms when DCFH is oxidized by these species, dichlorofluorescein
(DCF), allows for precise quantification of PM oxidative potential via spectrophotometry.
Rat alveolar macrophages (NR8383 cell line, RRID: CVCL_4396) obtained from the
American Type Culture Collection were maintained in Ham’s F12 medium (#11765-047,
ThermoFisher, Waltham, MA) supplemented with 2mM L-glutamine (GlutaMAX; #31765-035,
ThermoFisher, Waltham, MA), 1.176 g/L sodium bicarbonate, and 15% heat inactivated fetal
bovine serum (FBS; #45000-734, VWR, Radnor, PA). Cells were cultured in flasks and kept in
an incubator at 37 °C/5% CO2. Non-adherent cells were transferred to new flasks weekly. A
floating cell concentration of approximately 4 × 10
5
cells/mL media was maintained.
The DCFH assay involved placing 100 µL of macrophage cell suspensions (1,000 cells/µL)
into each well of a 96-well plate (100,000 cells/well) followed by incubation at 37 °C for two
hours. Three plates were prepared for each slurry treatment. Immediately prior to treatment, a
15mM solution of DCFH-DA prepared in N,N’-dimethyl formamide was diluted 1:10 to 1.5 mM
in salt glucose medium (SGM). 15 minutes prior to the end of the two-hour incubation period,
1.5 mM DCFH-DA solution was added to each sample slurry to reach a final concentration of 15
µM DCFH-DA for treatments. At the end of the two-hour macrophage incubation period, excess
media was removed from each 96-well plate, and 100 µL of the treatment slurry/DCFH-DA
solution was applied to the cells. Macrophage cells were exposed to each type of PM slurry
sample, am-PM2.5 (morning) and pm-PM2.5 (afternoon), for a period of 2.5 hours.
16

Fluorescence intensity following PM2.5 exposures was determined spectrophotometrically
using a CytoFlour II automated fluorescence plate reader (PerSeptive Biosystems, Framingham,
MA) at 504 nm excitation and 529 nm emission (Landreman et al., 2008; Shafer et al., 2010).
Zymosan (a β-1,3 polysaccharide of D-glucose) was used as a positive control in analyzing the
results of this assay because it binds to TLR-2 receptors on the alveolar macrophage cells, which
results in a reliably strong immunochemical response that can be quantified in fluorescence units
using the DCFH probe. The standard reporting units for this assay are thus μg-Zymosan/mg-PM.
The values reported by the laboratory represent the integration of three assay measurements from
a dilution series. Each of the dilution points is run in triplicate, so in effect, the single reported
value represents input from nine individual sample aliquot assays. The propagated uncertainty
value for each result (represented in the error bars of Figure 2.1) reflects standard deviation
components from the sample analysis, untreated control analysis (run paired with the sample),
and calibration uncertainty.
2.2.5 Microglia In Vitro Assays
2.2.5.1 BV-2 Cell Culture
For comparison with the alveolar macrophage assay, we conducted additional assays using
immortalized BV-2 cells (RRID: CVCL_0182), a microglial cell line used for studies of
neuroinflammation (Eun et al., 2017; Gresa-Arribas et al., 2012). BV-2 cells were cultured in
Dulbecco’s Modified Eagle’s Medium/Ham’s F12 50/50 Mix (DMEM F12 50/50; # 11320033,
Life Technologies, Carlsbad, CA) supplemented with 10% fetal bovine serum (FBS; #45000–
734, VWR, Radnor, PA), 1% penicillin/streptomycin (#P4333-100ML, Sigma-Aldrich, St.
Louis, MO), and 1% L-glutamine (GlutaMAX; #35050061, Life Technologies, Carlsbad, CA) in
a humidified incubator (37 °C/5% CO2). For cell treatments, PM2.5 slurries were diluted in the
17

same isotonic and pH-balanced culture media and applied to cells for up to 24 hours. Cell culture
experiments were conducted in triplicate for each analyzed endpoint.
2.2.5.2 Cytotoxicity Assay
The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay (Research
Products, Inc., Theodore, AL), allows for the quantification of cell mitochondrial activity by
spectrophotometrically detecting the presence of NAD(P)H-dependent cellular oxidoreductase
enzymes, which function as an index of cell viability. The assay was performed to initially assess
cytotoxicity at various PM treatment dosages ranging from 1 to 20 μg/mL. Cultured BV-2 cells
were plated at a concentration of 8x10
3
cells/well in 96-well plates and allowed to seed overnight
in order to achieve 60-70% confluency. Cells were then treated with 1, 2, 5, 10 & 20 μg/mL of
both morning and afternoon PM2.5, as well as a diluted media control, and then incubated at 37
°C in a 5% CO2 environment.
24 hours after PM treatments were applied, the cell media was removed and the MTT
reagent, prepared at a final concentration of 5 mg/mL in 1X phosphate-buffered saline (PBS),
was added to the cells (200μl/well), which were then incubated for an additional 4 hours in
darkness. The MTT reagent was then removed and 200 µL of 0.1N acidic isopropanol was added
to each well of cells to release and solubilize the formazan reagent, which is indicative of intact
mitochondria and thus viable cells. The quantity of formazan was measured by recording
changes in absorbance at 570 nm (with 630 nm used as the background wavelength) using a
microplate reading Spectra Max M2 spectrophotometer (Molecular Devices, San Jose, CA,
USA). The average net absorbance for each PM concentration in each exposure condition was
then compared with negative controls (method blanks) to determine normalized mitochondrial
18

reductase activity. Final values were represented as % change in mitochondrial reductase activity
relative to control.
2.2.5.3 Nitrite Assay
The Griess reagent for nitrite was used to assay nitric oxide (NO) released by the BV-2 cell
line (Ignarro et al., 1993), with NaNO2 (Sigma-Aldrich, St. Louis, MO, USA) used as a standard,
and untreated cell culture media as a blank control (Cheng et al., 2016b). Based on results of the
MTT assay, PM2.5 treatment concentrations of 1, 5 and 20 µg/mL were chosen to assess NO
production. BV-2 cells at 60-70% confluence in 96-well plates (2 x 10
6
cells/plate) were treated
with both am-PM2.5 and pm-PM2.5 at the specified doses, 200 µL/well. PM2.5 treatments were
prepared by diluting morning and afternoon slurry samples with isotonic and pH-balanced
culture media.
At 30-minute, 60-minute and 24-hour timepoints, 50 µL aliquots of cell media were removed
in duplicate from each treatment well and transferred to a new 96-well plate. Within the same
96-well plate, a series of nitrite standards (50 µL/well) ranging from 0.10 to 10 µM were
prepared from a NaNO2 stock solution, thus allowing a standardization curve to be generated for
use in determining the NO concentration in each treatment well from measured absorbance data.
To each well in the 96-well plate, 50 µL of Griess reagent was added and the plate was allowed
to incubate at room temperature (21–23 °C) for 10 minutes, followed by spectrophotometric
analysis at 548 nm absorbance using a SpectraMax M2 microplate reader (Molecular Devices,
San Jose, CA, USA). The nitrite assay was performed in triplicate, with six data points collected
at each PM2.5 concentration per condition.

19

2.2.5.4 Quantitative Polymerase Chain Reaction (qPCR)
The quantitative polymerase chain reaction (qPCR) assay was used to quantify upregulation
of cytokines and chemokines associated with the microglial neuroinflammatory response,
including IL-6, CCL2 (MCP-1), and IL-1β, by measuring the quantity of mRNA generated for
each gene after 24 hours of PM2.5 exposure. Cultured BV-2 cells were trypsinized and seeded in
six-well plates at 10
6
cells/well and grown overnight in a humid, 37 °C/5% CO2 environment.
Plated BV-2 cells were then treated with aqueous am-PM2.5 and pm-PM2.5 slurries diluted to 10
μg/mL in isotonic and pH-balanced cell culture media. A control condition, consisting of pure
media diluted with ultrapure water, was also prepared. After 24 hours of further incubation at 37
°C/5% CO2, treated cells were trypsinized and harvested for RNA extraction. Total cell RNA
was extracted using the Invitrogen TRIzol reagent (Carlsbad, CA, USA), and cDNA was
prepared from 1 μg of RNA (RT Master Mix, BioPioneer, San Diego, CA, USA). Specific
primers for each gene were used in conjunction with the qPCR master mix (BioPioneer) to run
real time qPCR reactions.
Genes examined by qPCR included IL-1β (forward: 5’ CTAAAGTATGGGCTGGACTG 3’;
reverse: 5’ GGCTCTCTTTGAACAGAATG 3’), IL-6 (forward: 5’
TGCCTTCTTGGGACTGATGCT 3’; reverse: 5’ GCATCCATCATTTCTTTGTAT 3’), MCP-1
(forward: 5’ CCCAATGAGTAGGCTGGAGA 3’; reverse: 5’ TCTGGACCCATTCCTTCTTG
3’), and GAPDH (forward: 5’ AGACAGCCGCATCTTCTTGT 3’; reverse: 5’
CTTGCCGTGGGTAGAGTCAT 3’) (Integrated DNA Technologies, Skokie, IL). Data were
normalized to GAPDH and quantified as ΔΔCt. qPCR was repeated once, for a total of twelve
data points collected in each treatment condition (am-PM2.5 and pm-PM2.5; 10 µg/mL).

20

2.3 Results
2.3.1 Alveolar Macrophage Assay
Results of the alveolar macrophage assay indicated a 6-fold larger acute oxidative stress
response in macrophage cells treated with am-PM2.5 (306 ± 52.2 µg-Zymosan/mg-PM) than in
cells treated with the pm-PM2.5 slurry (50.9 ± 33.0 µg-Zymosan/mg-PM), contrary to our
predictions (Figure 2.1).
Figure 2.1: Oxidative potential of PM 2.5 slurries by alveolar macrophage (DCFH) assay
Oxidative potential of particles was estimated by the macrophage DCFH in vitro assay. Results
normalized for total PM mass and reported in standard Zymosan units (µg-Zymosan/mg-PM). Mean
and SD values calculated from triplicate analysis of each sample.

2.3.2 Microglia Assays
2.3.2.1 Cytotoxicity (MTT) Assay
The mitochondrial reductase activity test (MTT) identified the effective concentration range
of PM2.5 treatments for further in vitro microglia assays, at a viability threshold of 50-70%
maximum cell metabolic activity. Microglial BV-2 cells were treated with four doses (1, 5, 10,
20 μg/mL) of morning and afternoon PM2.5 slurry samples, followed by 24 hours incubation
0
50
100
150
200
250
300
350
400
µg Zymosan Units / mg PM
Morning Afternoon
21

time. Significant reductions in mitochondrial activity relative to a control group were seen only
at the highest PM2.5 dose, i.e. 20 μg/mL, in both morning and afternoon treatment groups.
2.3.2.2 Nitrite Assay
Results were evaluated using 2-way repeated measures ANOVA statistical analysis and
Bonferroni post hoc tests. NO production relative to control was assessed as µM nitrite in
extracellular media by the Griess reaction. A dose-dependent NO response to am-PM2.5
treatments relative to control was observed at all timepoints. The induced NO response was
greater for am-PM2.5 than pm-PM2.5 treatments (Fig. 2.2). am-PM2.5 samples induced consistently
higher levels of NO for all concentrations and post-exposure timepoints. At 30 minutes post-
treatment, there was a significant effect of am-PM2.5, as well as a significant difference between
the responses to am-PM2.5 and pm-PM2.5 (overall ANOVA: p = 0.0017; am-PM2.5 20 µg/mL vs.
control: 5.3-fold increase, p = 0.0020; am-PM2.5 20 µg/mL vs. pm-PM2.5 20 µg/mL: 3.1-fold
increase, p = 0.0094). There was also a significant effect of am-PM2.5 at 60 minutes post-
treatment (overall ANOVA: p = 0.010; am-PM2.5 20 µg/mL vs. control: 7.0-fold increase, p =
0.0077). At 24 hours a significant effect of am-PM2.5 treatment was also observed (overall
ANOVA: p = 0.0005; am-PM2.5 20 µg/mL vs. control: 2.9-fold increase, p = 0.0007).
The NO responses to pm-PM2.5 paralleled the effect of am-PM2.5 exposures, but were at least
50% smaller: 20 µg/mL pm-PM2.5 induced 1.7-, 3.5-, and 2.0-fold increases in NO concentration
relative to control at 30 min., 60 min. and 24 hrs., respectively, but these effects were not
significant. There was also a significant difference between the responses to am-PM2.5 and pm-
PM2.5 observed at 30 minutes post-treatment, with morning PM2.5 eliciting a significant 3.1-fold
greater NO response than pm-PM2.5 (am-PM2.5 20 µg/mL vs. pm-PM2.5 20 µg/mL, p = 0.0094).

22

0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
30 min 60 min 24 hr
Normalized μM Nitrite (NO)
1 μg/mL
5 μg/mL
20 μg/mL
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
30 min 60 min 24 hr
1 μg/mL
5 μg/mL
20 μg/mL
Figure 2.2: Nitric oxide (NO) induction by microglia
BV-2 microglial responses to PM 2.5 slurries in vitro, assayed in culture media by the Griess reaction
(control = 1.0 µM nitrite, dashed line). A. Morning samples (am-PM 2.5); B. Afternoon samples (pm-
PM 2.5). Mean ± SE (n = 3 experiments). 2-way repeated measures ANOVAs with Bonferroni post hoc
tests: *p≤0.05, **p≤0.01, ***p≤0.001, ****p≤0.0001
A B

2.3.2.3 Quantitative Polymerase Chain Reaction (qPCR)
BV-2 cells were treated with 10 μg/mL of am-PM2.5 and pm-PM2.5 and analyzed for mRNA
responses by qPCR after 24 hours incubation. The 10 μg/mL dose was chosen as below threshold
for metabolic impairment, as determined by the MTT assay. Proinflammatory cytokines IL-1β,
IL-6, and the chemokine MCP-1, were chosen for analysis based on previous research
demonstrating their upregulation as induced by ultrafine PM (Woodward et al., 2017b; Morgan,
et al., 2011; Cheng et al., 2016b).
Results were evaluated using 2-way repeated measures ANOVA statistical analysis and
Bonferroni post hoc tests. Induction of all three cytokines was increased by both morning and
afternoon PM2.5 samples, with more modest responses to pm-PM2.5. As shown in Figure 2.3A,
treatment with am-PM2.5 induced a significant 4.8-fold increase in IL-1β expression relative to
control (overall ANOVA: p = 0.0090; am-PM2.5: 4.8-fold increase, p = 0.0070). Both am-PM2.5
**
***
**
am-PM 2.5
pm-PM 2.5

23

and pm-PM2.5 induced significant increases in IL-6 mRNA production (overall ANOVA: p <
0.0001; am-PM2.5: 5.1-fold increase, p < 0.0001; pm-PM2.5: 3.5-fold increase, p = 0.0050) (Fig.
2.3B). The am-PM2.5 treatment also induced a significant increase in MCP-1 mRNA production,
while pm-PM2.5 had a 33% smaller effect than am-PM2.5 (overall ANOVA: p = 0.0028; am-
PM2.5: 2.0-fold increase, p = 0.0022; am-PM2.5 vs. pm-PM2.5: p = 0.0527) (Fig. 2.3C).
Figure 2.3: Inflammatory gene mRNA induction in microglia
BV-2 cells were exposed to 10µg/mL of morning (am-PM 2.5) and afternoon (pm-PM 2.5) slurries, and
mRNA production was assessed by qPCR. Relative to control, both am-PM 2.5 and pm-PM 2.5
exposures increased mRNA levels of A. Interleukin 1β (IL-1β), B. Interleukin 6 (IL-6), and C.
monocyte chemoattractant protein 1 (MCP-1). Mean ± SE (n = 12). 2-way repeated measures
ANOVAs with Bonferroni post hoc tests: *p≤0.05, **p≤0.01, ***p≤0.001, ****p≤0.0001

A B C

2.3.3 Chemical Composition of PM2.5 Slurry Samples
The am-PM2.5 and pm-PM2.5 time-integrated aqueous slurry samples were analyzed for
chemical composition, including total carbon (TC), inorganic ions, and total metals and trace
elements. The results of these analyses are presented as PM2.5 mass fractions in Figures 2.4A,
2.4B, and 2.4C, respectively. TC content in the morning slurry was 0.50 μg/μg-PM, while in the
afternoon slurry it was 0.31 μg/μg-PM, a 40% decrease (Fig. 2.4A). Mass concentrations of
inorganic secondary ions (NO3
-
, SO4
2-
, NH4
+
, Na
+
), however, were higher in the afternoon as
compared to morning slurries (Fig. 2.4B).
**
**
**
24

For the sixteen metals and trace elements quantified by ICP-MS analysis, the am-PM2.5 slurry
contained higher mass concentrations of nearly all measured elements as compared to the pm-
PM2.5 slurry (Fig. 2.4C). Certain heavy metals (V, Cr, Ni, As) are emitted by vehicles, both as
fuel combustion products as well as remnants of motor oil degradation (Geller et al., 2006). Cu is
associated with vehicular brake wear (Sanders et al., 2003; Garg et al., 2000; Sternbeck et al.,
2002), and Zn is primarily a product of tire deterioration (Singh et al., 2002). Elevated levels of
these metals in both collection periods correspond to vehicular emissions as the major source of
primary particles in close proximity to the I-110 freeway.
Figure 2.4: Chemical analyses
Time-integrated PM 2.5 slurries collected during morning (6-9am) and afternoon (12-4pm) periods
analyzed for A. Total carbon (TC), B. Inorganic ions (ion chromatography), C. Total metals and trace
elements (ICP-MS). Mean values presented are based on triplicate analysis of one sample aliquot.
Error bars represent laboratory uncertainty values based on contributions of analytical error (standard
deviation) and blank subtraction (standard deviation of at least three method blanks).
A B

0.000
0.020
0.040
0.060
0.080
0.100
0.120
0.140
0.160
Nitrate Sulfate Ammonium Sodium
Concentration (ug/ug-PM)
Morning Afternoon
0
0.1
0.2
0.3
0.4
0.5
0.6
TC (µg/µg-PM)
Morning Afternoon
25

C

2.4 Discussion
Three independent in vitro assays of urban fine particulate matter (PM2.5) showed definitive
diurnal variations in PM2.5 oxidative potential and proinflammatory activity, with consistent
decreases from morning to afternoon sampling periods. Prior studies of diurnal variations in
oxidative stress due to PM exposures are largely based on eluted filter-trapped PM2.5 samples.
This study is greatly improved by utilizing a direct aerosol-into-liquid sampling technique to
more efficiently capture water-insoluble components of ambient PM2.5. Primary, traffic-derived
PM2.5 and secondary, photochemically aged PM2.5 samples were collected at a central Los
Angeles site and analyzed for chemical composition, oxidative potential, and inflammatory
responses due to oxidative stress. The alveolar macrophage assay was used to assess PM2.5
oxidative potential, and cellular inflammatory responses were assessed in BV-2 microglia via the
nitrite and qPCR in vitro assays. These findings are contrary to expectations based on prior
reports that secondary, photo-oxidized PM produces greater oxidative stress in cells than primary
PM (e.g. Verma et al., 2009).
1.0E-06
1.0E-05
1.0E-04
1.0E-03
1.0E-02
1.0E-01
1.0E+00
1.0E+01
As Ba Cd Co Cr Cu Fe K La Mn Mo Ni Pb Ti V Zn
Mass Fraction (ng/µg PM)
Morning Afternoon
26

Previous studies of oxidative stress induced by primary and secondary PM have not been
consistent and were limited by using only simple assays of filterable PM oxidative potential. For
example, Verma et al. (2009) examined the redox activity of filterable ultrafine PM (Dp < 0.18
μm) collected in the summer of 2008, at the same USC location adjacent to the Los Angeles I-
110 freeway, during morning (6-9am) and afternoon (11am-4pm) time periods. The oxidative
potential of both types of PM collected was quantified by the dithiothreitol (DTT) chemical
assay and found to be significantly higher in afternoon samples (average morning-to-afternoon
ratio, am:pm = 0.56). In this same study, the cellular oxidative stress as measured by the alveolar
macrophage assay did not show a significant difference between morning and afternoon samples,
though the trend was the same (am:pm = 0.83). Of the three pairs of morning vs. afternoon
samples compared using the alveolar macrophage assay, results of one comparison did, however,
show the morning PM sample to exhibit substantially more oxidative potential than the afternoon
PM sample (am:pm = 1.7).
Saffari et al. (2015) also examined the oxidative potential of ultrafine particulate matter (Dp
< 0.25 μm), collecting filterable ultrafine PM samples at 3 locations in the greater Los Angeles
area. The sampling locations included the same USC PIU site used by Verma et al. (2009) and in
the current study, a coastal site in Long Beach, CA, near the I-710 freeway, which is heavily
impacted by heavy-duty truck traffic, and an inland site in Upland, CA, approximately 35 miles
east of downtown Los Angeles. Sampling was conducted at the coastal site during the morning
rush hour period (6-10am), at the PIU during midday (10am-2pm), and at the inland site in the
afternoon (2-6pm). In that study, the alveolar macrophage assay was used to determine the mass-
based oxidative potential associated with in vitro PM exposure. In contrast to Verma et al.
(2009), the morning samples collected at the coastal site proximal to the I-710 freeway had the
27

highest oxidative potential (10,277 ± 1,669 µg-Zymosan/mg-PM). The next highest redox
activity was associated with the midday PM samples collected at the central USC site (8,213 ±
1,892 µg-Zymosan/mg-PM), followed by the lowest activity exhibited by the inland afternoon
samples (6,677 ± 1,615 µg-Zymosan/mg-PM). These results indicated decreasing PM redox
activity moving from coastal (morning) to inland (afternoon) sampling sites (am:pm = 1.5).
Using source apportionment to attribute increased oxidative potential to specific PM species,
Saffari et al. (2015) also showed that the redox activity elicited in response to coastal (morning)
PM was driven by primary, traffic-derived particles, enriched in transition metals and water-
insoluble organic carbon (WIOC) compounds such as polycyclic aromatic hydrocarbons (PAHs).
The oxidative potential of inland (afternoon) PM samples, however, was driven by species found
in secondary, photochemically-oxidized PM, including secondary organic aerosols (SOA) that
contain a high fraction of polar water-soluble organic carbon (WSOC) compounds.
The current study improves on the experimental design of past studies of diurnal variations
by assessing direct measures of acute oxidative stress and inflammation, including free radical
production induced by PM as nitric oxide (NO) and cellular mRNA responses. Relying solely on
simple oxidative potential measures such as the DTT and alveolar macrophage assays provides
us with only an imprecise measure of the cellular proinflammatory response that lacks specificity
(Forman and Finch, 2018). Additionally, by using the direct aerosol-into-liquid method to collect
aqueous slurries, water-insoluble PM species are more efficiently captured, providing samples
more representative of the full range of ambient PM components and their toxicities.
Further insight into the sources of particulate toxicity may be gleaned by the apportionment
of redox properties to its water soluble and insoluble chemical components, including water-
soluble and water-insoluble organic carbon (WSOC and WIOC, respectively). WSOC species
28

are generally defined as hydrophilic, while WIOC are hydrophobic (Turpin & Lim, 2001). Wang
et al. (2013b) also collected aqueous PM2.5 slurries by the aerosol-into-liquid sampling method,
and found that increased WIOC content in PM2.5, relative to WSOC content, was highly
correlated with redox activity on a per mass basis, indicating a greater intrinsic toxicity of WIOC
as compared to WSOC. The increased oxidative potential associated with increased WIOC mass
concentrations was attributed to organic compounds, as well as iron and other metals.
Our results indicate that morning PM2.5, which contains a greater proportion of water-
insoluble species that are more efficiently captured by the direct aerosol-into-liquid collection
system, may be intrinsically more toxic, and induce greater oxidative stress in cells, than
afternoon PM2.5 samples that contain a larger mass fraction of oxidized, water-soluble species.
The mechanism underlying this toxicity may involve water-insoluble non-polar components (i.e.
WIOC) of PM2.5, such as PAHs, being able to more easily permeate the hydrophobic lipid-
bilayer of cell membranes, and then trigger the formation of intracellular oxidative species and
proinflammatory cytokines via an acute oxidative stress response. Primary, traffic-derived PM2.5
also consists of greater concentrations of redox active and other toxic metals, as compared to the
bulk of secondary PM2.5, which consists largely of hydrophilic products of photochemical
oxidation. We conclude the higher proportion of these metals and WIOC components in primary
PM2.5 dominant in the morning hours, as compared to photo-oxidized secondary PM2.5 prevalent
in the afternoon, is responsible for the diurnal variation in acute oxidative stress observed in the
current study.
2.5 Summary and Conclusions
This study demonstrates that urban particulate matter collected during the morning rush hour
(6-9am), when primary, traffic-derived PM2.5 emissions are dominant, induces greater oxidative
29

stress in cells as compared to particulate matter collected in the afternoon (12-4pm), which
contains a high proportion of photo-oxidized, secondary PM2.5 products. Results of three in vitro
assays of the cellular inflammatory response provide converging evidence for this diurnal
variation in oxidative stress due to PM2.5 exposure. We attribute this effect to the greater
transition metal and WIOC content of primary PM2.5, two classes of particulate components that
can increase toxicity. Our study also improves upon previous research of diurnal variations in
PM-induced oxidative stress by utilizing a unique aerosol-into-liquid PM collection system that
more efficiently captures water insoluble components, thus providing more complete aqueous
PM samples. This research will ultimately help us gain a more complete understanding of the
complex nature of particulate matter and how its composition and proinflammatory effects
change over time due to photochemical aging in the atmosphere. The Southern California climate
of Los Angeles with abundant sunshine, compounded with dense vehicular traffic, generates
ubiquitous primary and secondary PM throughout the year. Identifying the health effects of these
pollutants is critical as we strive to understand the underlying mechanisms of PM-induced
oxidative stress, neuroinflammation and associated morbidity. Our findings may help in further
elucidating the role of PM in the etiology, onset and development of widespread, chronic
diseases that plague global populations, including cancer, cardiac and respiratory distress, and
neurodegenerative disorders such as Alzheimer’s disease.
30

Chapter 3

Cancer and Non-Cancer Health Risks to Los Angeles Commuters:
Roadway, Light-Rail, and Subway Transit Routes

Residents of the megacity of Los Angeles are exposed to significant amounts of airborne
particulate matter (PM) during their daily commutes, which often exceed 30-60 minutes each
way. Chemical species present in roadway and railway PM, including benzo[a]pyrene (BaP), and
hexavalent chromium (Cr
6+
), present substantial cancer and non-cancer health risks. In the
current study, PM samples were collected and quantitatively speciated along five major
commuter routes, including the METRO red line (subway) and gold line (light rail), the I-110
and I-710 freeways, and high-density surface streets (Sunset and Wilshire Boulevards). Using
these concentration data, along with cancer potency (CP) and Reference Dosage (RfD) factors
obtained from the United States Environmental Protection Agency (USEPA) and California's
Office of Environmental Health Hazard Assessment (OEHHA), cancer and non-cancer health
risks were calculated. In contrast to previous research indicating that polycyclic aromatic
hydrocarbon (PAH) components of Los Angeles roadway PM (e.g. along the I-710 freeway) led
to the greatest cancer risk, the current analysis reveals that exposure to carcinogenic transition
metals, particularly hexavalent chromium, which are especially prevalent along the METRO red
line, results in the greatest cancer and non-cancer health risks. Based on these data, the best
option for commuters is to use above-ground light-rail transportation, which allows for reduced
exposure to both traffic-generated PAHs and railway-related metals.
This chapter is based on the following publication:
Lovett, C., Shirmohammadi, F., Sowlat, M. H., & Sioutas, C. (2017). Commuting in Los Angeles: Cancer
and non-cancer health risks of roadway, light-rail and subway transit routes. Aerosol and Air Quality
Research, 18, 2363-2374. DOI: 10.4209/aaqr.2017.09.0331

3.1 Introduction
In megacities such as Los Angeles, Seoul, Tokyo, Moscow, Tehran, and São Paulo, whose
populations exceed 10 million inhabitants, commuters rely heavily on public transportation,
31

including bus, subway and light-rail transit systems, as well as personal vehicles. All modes of
transportation, however, expose the public to varying degrees of air pollution during their daily
commute, and the concomitant health risks can be significant. Airborne particulate matter (PM)
is considered one of the most toxic forms of air pollution to which commuters are typically
exposed, in both roadway and railway environments. PM2.5, or fine particulate matter, which
includes all PM smaller than 2.5 µm in diameter, is largely the product of condensation and
agglomeration of primary ultrafine particles emitted by a variety of combustion sources, and
results in more deleterious health effects due to its small size allowing for deep penetration into
the lungs and subsequently the bloodstream (Brugge et al. 2007; Delfino et al., 2010; de Kok et
al., 2006).
PM2.5 is composed of multiple chemical species, including carbonaceous materials such as
elemental and organic carbon (EC/OC), crustal elements, organic compounds, transition metals,
hopanes and steranes, and vehicular abrasion detritus. Two classes of compounds commonly
found in the airborne PM to which commuters are exposed, polycyclic aromatic hydrocarbons
(PAHs) and transition metals, contain species known to be carcinogens and/or pose chronic
health risks (Harrison et al., 2004). Polycyclic Aromatic Hydrocarbons (PAHs), such as
Benzo(a)pyrene (BaP), are formed during incomplete fossil fuel combustion and are typically
found in the PM emitted by vehicles. Transition metals, including nickel (Ni), iron (Fe), and
hexavalent chromium (Cr
6+
), often result from the friction-induced wear of railway components,
especially steel rails and cables, and thus represent a significant fraction of light-rail and subway
PM emissions (Seaton et al., 2005; Chillrud et al., 2004).
Several recent research programs investigating roadway, light-rail and subway PM exposures
have been conducted in various megacities and other large urban cities throughout the world.
32

These studies include investigations of airborne metals concentrations in the New York subway
system (Chillrud et al., 2004; Grass et al., 2010), the measurement of PM10 and PM2.5
concentrations both on platforms and inside railway cars of above and below ground metro trains
in Naples, Italy (Carteni et al., 2015), a quantification of PM2.5 exposure and metals content in
the subways of Helsinki (Aarnio et al., 2005), a comparison of roadway and railway PM2.5
exposures in Mexico City (Gomez-Perales et al., 2004) and London (Adams et al., 2001), as well
as studies of subway PM exposures in Milan (Colombi et al., 2013), Barcelona (Martins et al.,
2015; Moreno et al., 2015), and Shanghai (Lu et al., 2015).
Typically, higher concentrations of airborne PM have been found in subway systems as
compared to above-ground railway systems and roadways. Within the subway systems, PM
concentrations were found to be higher at the waiting platforms as compared to within the
railway cars, which are often enclosed and well-ventilated. Additionally, studies that evaluated
subway and light-rail PM speciation (e.g. Chillrud et al., 2004; Grass et al., 2010; Aarnio et al.,
2005; Colombi et al., 2013; Lu et al., 2015; Moreno et al., 2015) found higher concentrations of
metals, especially Fe, Mn, Cu, Cr and Ni, in the PM collected on subway lines, compared to
particulate collected in above-ground ambient conditions, as well as during light-rail and
roadway exposures. The high metal content of subway PM has been attributed to the wear of
railway components, including steel cables, wheels, and rails, as well as braking systems, and
higher PM concentrations at subway platforms result from the resuspension of “steel dust” and
other PM by passing trains.
Historically considered one of the most polluted megacities in the world, Los Angeles has a
unique composition of commuters. As a city consisting of a vast, decentralized urban sprawl with
a multitude of business and manufacturing hubs interspersed throughout numerous residential
33

communities, its workers must utilize an extensive latticework of arterial railways, roadways and
freeways to make their daily commutes between their homes and places of employment. Perhaps
more than any other megacity, a large percentage of Los Angeles commuters choose to travel via
personal vehicles in addition to using public transit. Nearly 90% of the 4.5 million workers in
Los Angeles and its surrounding areas spend an average of 60 minutes per day commuting on a
roadway or railway (U.S. Census Bureau, 2015 American Community Survey), and the
cumulative health risk posed by the airborne particulate matter (PM) to which they are exposed
is significant.
Several recent studies of air pollution along the various commuter pathways, both road and
railway, in Los Angeles have examined the composition and characteristics of particulate matter
to which commuters are exposed. These studies have focused on vehicular roadways (Kam et al.,
2012; Shirmohammadi et al., 2017; Vreeland et al., 2017; Zhu et al., 2007), as well as light-rail
and subway transportation systems (Kam et al., 2011a, 2011b), and have also compared the
relative PM exposures, compositions, and health risks associated with each mode of transport
(Kam et al., 2013). Two factors are key in determining the impact of toxic PM compounds on
commuters, as quantified by standard health risk indices such as Extended Life Cancer Risk
(ELCR) and the non-cancer Hazard Quotient (HQ): the duration of PM exposure and the inherent
PM toxicity as determined by its specific chemical composition.
Kam et al. (2013), in examining the cancer risk to Los Angeles commuters posed solely by
PAHs, collected samples of filterable particulate matter < 2.5 μm in diameter (PM2.5) along five
major commuting routes, including an above-ground light-rail train route (METRO gold line), a
below-ground subway line (METRO red line), two major freeways with high (11.3%) and low
(3.9%) volumes of heavy-duty vehicle (HDV) traffic (I-710 and I-110, respectively), and high
34

traffic volume surface streets (Wilshire and Sunset Boulevards). These authors found that I-710,
with its large volume of HDV traffic and corresponding high PAH concentrations in collected
PM2.5, posed the greatest health risk (i.e. lung cancer risk) to commuters, 1.8-4.5 times higher
than that resulting from PM exposure on other commuter routes.
While the research of Kam et al. (2013) focused on the cancer risks resulting exclusively
from the PAH content of PM2.5 to which commuters are exposed, transition metals, such as
nickel, chromium and cobalt, also contribute significantly to cancer, as well as non-cancer,
health risks. Diesel exhaust particulate (DEP), a specific subset of PM composed largely of
PAHs and elemental carbon (EC), or black carbon, presents a significant health risk to
commuters as well. While PAH components of PM increase cancer risk due to their
mutagenic/carcinogenic properties, the EC fraction contributes to cancer risk by distinct non-
genotoxic, tumor-promoting mechanisms such as increased inflammation and reactive oxygen
species (ROS) formation (Sauvain et al., 2003). The risks posed by metals and EC were not
included in the Kam et al. (2011a, 2011b, 2012) studies. However, in the current study, we detail
the contributions of both PAHs and transition metals, as well as EC, to both cancer and non-
cancer risks, thus presenting a more comprehensive picture of the health hazards to commuters
resulting from exposure to toxic species of airborne PM2.5 in the megacity of Los Angeles.
3.2 Methodology
3.2.1 Sampling Methods
The PM2.5 data reviewed in the current study were collected along the Los Angeles METRO
gold (light-rail) and red (subway) lines during the months of May through August 2010 (Kam et
al., 2011a), and on two major freeways (I-110 & I-710) and surface streets (Wilshire/Sunset)
during the months of March through May 2011 (Kam et al., 2012). All PM2.5 samples were
35

collected using Personal Cascade Impact Samplers, or PCISs (SKC Inc., Eighty-Four, PA; Misra
et al., 2002; Singh et al., 2003), in conjunction with Leland Legacy portable pumps (SKC Inc.,
Eighty-Four, PA) set at an air intake flow rate of 9 liters per minute (lpm). PM2.5 samples were
collected for chemical speciation on either Teflon (PTFE) filters (Pall Life Sciences, Ann Arbor,
MI) or quartz microfiber filters (Whatman International Ltd., Maidstone, England) placed
downstream of the 2.5 μm cut-point impactor stage in each PCIS.
Two separate sets of filters samples were collected along each of the five sampling routes (2
freeways, 2 railways, 1 surface street route) for chemical analysis. For the on-road sampling
campaign, 6 PCISs were utilized (3 equipped with Teflon filters, 3 with quartz filters) per set.
Sampling at each location was conducted over 5 consecutive weekdays, from 6:00 AM to 5:00
PM each day, using a 2011 Honda Insight Hybrid as a mobile test vehicle. Ambient air intake to
the 6 PCISs was through a 3/8-inch diameter stainless steel inlet nozzle affixed to the vehicle,
with the opening positioned towards the front (i.e. directly into oncoming roadway air flow). Due
to variable driving speeds, depending on traffic conditions, roadway sampling was necessarily
anisokinetic. However, as discussed in Kam et al. (2012), PM2.5 sampling at typical roadway
driving speeds of 10-50 mph is not significantly affected by any corresponding deviations from
isokineticity.
For the light-rail and subway sampling, 3 PCISs were employed by each experimenter (2
with Teflon filters, 1 with a quartz filter). Each set of filter samples was collected over 7
weekdays, from 9:30 AM to 1:00 PM, while experimenters spent approximately 25% of this time
on the railway platform and 75% of the time riding the train. To collect ambient air samples
during their commute, each experimenter was equipped with a carry-on suitcase containing the 3
36

PCISs and 3 pumps. Commutes included stopping at two stations along the route, which varied
week-to-week, for platform sampling.
3.2.2 Sampling Locations and Route Descriptions
Figure 3.1: Los Angeles commuter routes

37

An overview of the five commuter routes along which samples were collected is presented
above in Figure 3.1, with relevant route parameters presented in Table 3.1. More detailed
descriptions of the METRO train routes and sampling protocol have been detailed in Kam et al.
(2011a), while the specifics of roadway sampling on the freeways and surface streets have been
described in Kam et al. (2012).
Table 3.1: General characteristics of the investigated sampling routes
Characteristics
METRO
Gold line
METRO
Red line
I-110
Freeway
I-710
Freeway
Wilshire/
Sunset
Length of sampling
route
32 km 26 km 51 km 43 km 48 km
Sampling dates
May-Aug
2010
May-Aug
2010
March-April
2011
March-April
2011
March-May
2011
Traffic flow
(vehicles/hr)
- - 6378 4247 1839
Percentage of
HDVs (%)
- - 3.9 11.3 -
Sampling type
Platform &
in-train
Platform &
in-train
Vehicle-
based
Vehicle-
based
Vehicle-
based

Briefly, the two METRO lines discussed in the present study are electric-powered, third-rail
train lines linking downtown Los Angeles to outlying areas of the city. The METRO gold line is
an above-ground light-rail train line running between East Los Angeles, Downtown, and
Pasadena to the north, with 21 stations scattered along its 32 kilometer length. The METRO red
line is a below-ground subway line connecting downtown Los Angeles to North Hollywood,
with 14 stations along its 26.4 kilometer length. Unlike other subway systems in the world, the
subway and light-rail trains in LA operate with mandatory closed windows the train cabins and
are mechanically ventilated. Thus, the METRO trains represent the most protective travel
configuration for commuter PM exposures.
38

The I-110 and I-710 Los Angeles freeways are both high-density roadways that connect
commuters living in outlying communities to the urban hub of downtown Los Angeles (DTLA)
as well as other major business districts. I-110 is a 51-kilometer north-south freeway connecting
San Pedro and the Port of Los Angeles in the south to Pasadena in the north, passing along the
western edge of DTLA. I-710 (also known as the Long Beach Freeway) is a 43-kilometer north-
south freeway, parallel to and east of I-110, that begins in Long Beach at its southern end and
ends in Pasadena to the north, running along the eastern edge of DTLA. The I-710 freeway
experiences a lower volume of traffic (4247 vehicles per hour) as compared to the I-110 (6378
vehicles per hour), however the I-710 freeway traffic consists of a higher percentage of heavy-
duty trucks (11.3%) as compared to the I-110 freeway (3.9%). Wilshire and Sunset Boulevards
are major east-west surface streets with a moderate vehicle density (1839 vehicles per hour, with
negligible truck traffic). During the roadway sampling campaign, a 48-km route was traversed
along these streets, passing through the communities of Beverly Hills, Hollywood, Echo Park,
Koreatown, and DTLA.
As a quasi-control condition, PM emissions and composition were also determined at a
stationary urban site in central Los Angeles, adjacent to the main campus of USC. Filter samples
were collected utilizing 3 PCISs (2 with Teflon filters, 1 with a quartz filter), as described
previously, at a stationary laboratory near DTLA, the USC Particle Instrumentation Unit (PIU).
These filter samples were collected concurrently during the time periods of both the roadway and
railway sampling campaigns, using the same procedures, and underwent the same chemical
analyses, as is further detailed in Kam et al. (2011a, 2012).

39

3.2.3 Sample Analysis
Gravimetric analysis consisted of weighing all filters pre- and post-sampling with an MT5
Microbalance (Mettler-Toledo Inc., Columbus, OH) to determine mass loading. PM total metals
content was determined by analyzing the Teflon filters using magnetic-sectored Inductively
Coupled Plasma Mass Spectroscopy (SF-ICPMS) after acid extraction (Zhang et al., 2008). To
determine the PAH species present in the collected PM samples, gas chromatography/mass
spectroscopy analysis was performed on the quartz filter samples (Mazurek et al., 1987; Schauer
et al., 1999). Quartz filters were also analyzed for elemental carbon (EC) using Thermal
Evolution/Optical Transmittance analysis (Birch and Cary, 1996).
3.2.4 Cancer and Non-Cancer Risk Calculations
While several PAHs encountered by commuters are carcinogenic, as discussed in Kam et al.
(2012), this type of airborne particulate matter is also composed of several transition metals that
present a significant cancer risk (Klein, 1996), particularly hexavalent chromium (Cr
6+
), which is
the oxidation state of chromium that has been shown to dominate airborne PM emissions
resulting from high temperature processes such as welding and combustion (Shi et al., 1994;
Edme et al., 1997). In the current study, we examined and quantified the cancer risk associated
with exposure to both PAHs and metals, as well as the chronic health hazards such materials
pose. Additionally, we assessed the cancer risk posed by Diesel Exhaust Particulate (DEP) using
Elemental Carbon (EC) concentration as a surrogate index of DEP concentration as described in
Sauvain et al. (2003).
To calculate the cancer risk to humans, quantified as Excess Lifetime Cancer Risk (ELCR),
as well as the chronic non-cancer risk, quantified as the Hazard Quotient (HQ), we first
calculated the Chronic Daily Intake (CDI) of each compound at each sampling location. The
40

CDI, in units of mg/kg-day, was calculated from the toxin concentration (mg/m
3
), daily intake
rate based on a 1-hour daily commute (20 m
3
/day x (1hr/24hr)), days of exposure per lifetime (5
days/week x 50 weeks/year x 30 years of employment), average human body weight (70 kg), and
average human lifetime (70 years), as detailed in Equation (3.1).
3.2.4.1 Chronic Daily Intake (CDI):

ear) 365(days/y x e) (years/lif 70 x (kg) t Body Weigh
) (days/life Exposure x /day) (m Rate Intake x ) (mg/m ion Concentrat
3 3
= CDI
(3.1)

Intake rate: 20 m
3
/day x 1 hr/day commute x day/24 hrs = 0.833 m
3
/day

Exposure: 5 days/week x 50 weeks/year x 30 years = 7500 days/life

Body weight: 70 kg

3.2.4.2 Excess Lifetime Cancer Risk (ELCR):
The CDI for each compound was then multiplied by its Cancer Potency (CP) factor, in units
of (mg/kg-day)
-1
, to calculate lifetime cancer risk, or ELCR, as detailed in Equation (3.2).

-1
day) - (mg/kg factor potency * day) - (mg/kg CDI = ELCR (3.2)

There is some discrepancy in CP factors between those provided by the United States
Environmental Protection Agency (USEPA), which are listed in their Integrated Risk
Information System (IRIS) database, and those provided by California’s Office of Environmental
Health Hazard Assessment (OEHHA). In the current study, distinct ELCR values were
calculated for each compound using both the USEPA and OEHHA CP factors. If only a single
CP factor was available (from either agency) that value was used in both calculations. CP factors
from both the USEPA and OEHHA are presented in Table 3.2.

41

Table 3.2: Cancer Potency (CP), Reference Concentration (RfC) and Reference Exposure Level
(REL) for selected PAHs and metals
Compound CAS No.
CP (USEPA)
(mg/kg-day)
-1

CP (OEHHA)
(mg/kg-day)
-1

RfC (EPA)
(mg/m
3
)
REL (OEHHA)
(mg/m
3
)
PAHs
Benz(a)Anthracene 56-55-3 NA
a
0.39 NA NA
Benzo(a)Pyrene (BaP) 50-32-8 2.1 3.9 2.0 x 10
-6
NA
Benzo(b)Fluoranthene 205-99-2 NA 0.39 NA NA
Benzo(j)Fluoranthene 205-82-3 NA 0.39 NA NA
Benzo(k)Fluoranthene 207-08-9 NA 0.39 NA NA
Chrysene 218-01-9 NA 0.039 NA NA
Dibenz(ah)Anthracene 53-70-3 NA 4.1 NA NA
Dibenzo(ae)Pyrene 192-65-4 NA 3.9 NA NA
Indeno(1,2,3-cd)Pyrene 193-39-5 NA 0.39 NA NA
Metals
Aluminum 7429-90-5 NA NA 5.0 x 10
-3
NA
Arsenic, inorganic 7440-38-2 15.05 12.0 NA 1.5 x 10
-5

Cadmium 7440-43-9 6.3 15.0 2.0 x 10
-6
2.0 x 10
-5

Chromium (VI) 18540-29-9 42.0 510 1.0 x 10
-4
2.0 x 10
-4

Cobalt 7440-48-4 31.5 NA NA NA
Copper 7440-50-8 NA NA NA NA
Lead 7439-92-1 0.040 0.042 1.5 x 10
-4
NA
Manganese 7439-96-5 NA NA 5.0 x 10
-5
9.0 x 10
-5

Nickel 7440-02-0 0.84 0.91 NA 1.4 x 10
-5

a
NA: Not assessed

Individual ELCRs for each species, both metals and PAHs, were summed to generate a Total
ELCR value for each sampling location. As with individual ELCR values, Total ELCR values
were calculated from both the USEPA- and OEHHA-based ELCR values and reported
separately. A Maximum Total ELCR value was calculated for each location by summing only
the higher of the two individual ELCR values for each compound. The Maximum Total ELCR
value for each site also includes the calculated cancer risk due to DEP. The threshold for
acceptable cancer risk is generally defined as 1 in a million, or 10
-6
, per most governmental
health and environmental organizations, e.g. the World Health Organization (WHO), USEPA,
42

OEHHA, and the South Coast Air Quality Management District (SCAQMD), the regional air
quality regulatory agency with jurisdiction over Los Angeles county and adjoining areas.
Cancer risk due to DEP exposure (using EC as a surrogate of DEP, as noted earlier) was
calculated using the method described in Sauvain et al. (2003) and Stayner et al. (1998). In this
method, the EC concentration is multiplied by the Inhalation Unit Risk (IUR) factor to give
cancer risk. An IUR value is defined by the USEPA’s Integrated Risk Information System (IRIS)
as “The upper-bound excess lifetime cancer risk estimated to result from continuous exposure to
an agent at a concentration of 1 µg/m³ in air,” (https://www.epa.gov/iris). To calculate cancer
risk resulting from occupational DEP (EC) exposure over an 8-hour work day, Sauvain et al.
(2003) used an IUR of 2.8 x 10
-6
(µg/m
3
)
-1
based on rodent exposure toxicology data and
corrected for an 8-hour workday and 45-year working period. For use in calculating commuter
exposure risk, we divided this value by eight, resulting in a 1-hour commuter IUR of 3.5 x 10
-7

(µg/m
3
)
-1
.
Cancer risk calculated using IUR values represents the upper-limit of risk and does not take
into account body weight, which is factored into the cancer potency values used to calculate
ELCR. Additionally, it should be noted that unit risk values vary widely based on
epidemiological and toxicological studies, as discussed in Stayner et al. (1998), and no best
method of determining IUR values has been agreed upon. Calculating ELCR using cancer
potency values provided by OEHHA and USEPA, along with the CDI value, which incorporates
several exposure factors such as body weight and breathing rate, is a more robust method of
cancer risk determination. Sharma & Balasubramanian (2017) in their paper examining wildfire
smoke haze-related PM2.5 health risks in Southeast Asia, in both indoor and outdoor
environments, also use this method of calculating ELCR values and calculate cancer risks. Their
43

results (e.g. a 3.4 to 5.8 x 10
-6
cancer risk due to the Cr component of PM2.5 during outdoor haze
exposures) are comparable in magnitude to the findings of the current study.
3.2.4.3 Hazard Quotient (HQ):
To calculate the chronic (lifetime) non-cancer risk, or Hazard Quotient (HQ), the same CDI
used for cancer risk calculations is divided by the Reference Dosage (RfD), in units of mg/kg-
day, as shown in Equation (3.3). The RfD is calculated from either the inhalation exposure
Reference Concentration (RfC) values provided by the USEPA, or the chronic Reference
Exposure Level (REL) values provided by OEHHA. Both RfC and REL concentration values
are provided in units of mg/m
3
. To calculate RfD values, the RfC or REL is multiplied by the
human daily inhalation rate of 20 m
3
/day and divided by the average human body weight of 70
kg. As with ELCR values, in calculating non-cancer health hazard values, the available RfC or
REL value was used, or, when both were available, two distinct HQ values were determined, one
using the USEPA RfC and one using the OEHHA REL. RfC and REL values are presented in
Table 3.2.

day) - (mg/kg RfD
day) - (mg/kg CDI
= HQ
(3.3)

EPA: RfD = RfC (mg/m
3
) x Inhalation Rate (20 m
3
/day) / Body Weight (70 kg)

OEHHA: RfD = REL (mg/m
3
) x Inhalation Rate (20 m
3
/day) / Body Weight (70 kg)

3.3 Results and Discussion
3.3.1 Particulate Matter Composition at Sampling Sites
General parameters of the various sampling routes and collection periods are presented in
Table 3.1. While the total volume of vehicular traffic along the I-110 freeway (6378 vehicles/hr)
44

was larger than that along the I-710 freeway (4247 vehicles/hr), the percentage of HDV trucks on
the I-710 (11.3%) was significantly higher than on the I-110 freeway (3.9%).
Transition metals posing a cancer risk to commuters that were detected in measurable
concentrations at any of the test sites include As, Co, Cd, Cr, Pb and Ni, while the detectable
metals contributing to non-cancer risk include Al, As, Cd, Cr, Ni, Pb and Mn. Airborne PAHs
having an associated cancer risk that were detected along any of the commuter sampling routes
include benz(a)anthracene, benzo(a)pyrene (BaP), benzo(b)fluoranthene, benzo(k)fluoranthene,
chrysene and indeno(1,2,3-cd)pyrene. The only detected PAH with an associated non-cancer
health hazard risk was BaP, however this compound was only found in PM samples collected
along the I-710 freeway.
Concentrations (ng/m
3
) of relevant transition metal and PAH species contained in PM
captured at these sampling sites are presented in Table 3.3. As seen in Table 3.3, the highest
concentrations of transition metals, particularly aluminum (151 ± 47.5 ng/m
3
), manganese (84.9
± 13.1 ng/m
3
), copper (64.8 ± 11.3 ng/m
3
), and chromium (23.1 ± 4.7 ng/m
3
), were found in PM
samples collected along the METRO red line commuter pathway. These values are lower but
comparable to those found by Chillrud et al. (2004) for manganese (240 ng/m
3
) and chromium
(84 ng/m
3
) during their study of the New York City subway system. These authors note that
while the manganese and chromium (VI) concentrations measured are much lower than the
permissible exposure levels (PELs) set by the Occupational Safety and Health Administration
(OSHA), namely 5,000 ng/m
3
for Cr (VI) and 200,000 ng/m
3
for Mn (8-hr averages), the
calculated total excess lifetime cancer risk at the measured concentrations is greater than 10
-5
,
clearly posing a substantial cancer risk that exceeds the ELCR safety threshold of 10
-6
.
45
Table 3.3: Summary statistics of the concentrations (ng/m
3
) of chemical components (metals, PAHs, & EC) measured in each sampling campaign
Category Species
Gold line Red line I-110 I-710 Wilshire/Sunset USC
Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD
Metals
Al 61.7 54.6 151 47.5 197 ND 182 ND 170 ND 136 11.0
As 0.382 0.191 0.877 0.0833 0.659 ND 0.394 ND 0.491 ND 0.453 0.0725
Cd 0.127 0.0674 0.985 0.113 0.153 ND 0.113 ND 0.136 ND 0.0865 0.0170
Cr 2.14 0.932 23.1 4.75 4.13 ND 3.44 ND 3.274 ND 3.03 1.54
Co 0.102 0.0257 1.24 0.219 0.1634 ND 0.167 ND 0.158 ND 0.132 0.0324
Cu 37.5 2.52 64.8 11.3 60.4 ND 36.8 ND 43.3 ND 14.4 0.760
Pb 2.37 1.13 2.89 0.350 4.73 ND 3.99 ND 4.92 ND 3.35 0.786
Mn 5.81 2.15 84.9 13.1 9.97 ND 9.16 ND 7.45 ND 5.10 0.632
Ni 1.42 0.482 11.9 2.56 1.74 ND 1.61 ND 0.912 ND 2.47 1.31
PAHs
Benz(a)Anthracene 0.0208 ND
a
NA -- 0.0955 0.0251 0.157 0.0557 0.0590 0.0218 0.0137 0.0122
Benzo(a)Pyrene NA
b
-- NA -- NA -- 0.0886 0.0479 NA -- NA --
Benzo(b)Fluoranthene 0.1217 ND

0.0958 0.0148 0.313 0.0538 0.300 0.0870 0.233 0.0689 0.0945 0.0600
Benzo(j)Fluoranthene NA -- NA -- NA -- NA -- NA -- NA --
Benzo(k)Fluoranthene 0.0440 ND 0.0523 0.0002 0.102 0.0114 0.104 0.0675 0.0485 0.0193 0.0308 0.0211
Chrysene 0.194 ND 0.140 0.0224 0.228 0.0621 0.253 0.0738 0.135 0.0100 0.0911 0.0757
Dibenz(ah)Anthracene NA -- NA -- NA -- NA -- NA -- NA --
Dibenzo(ae)Pyrene NA -- NA -- NA -- NA -- NA -- NA --
Indeno(1,2,3-cd)Pyrene 0.0475 ND 0.0649 0.0032 0.0916 0.0626 0.0371 0.0143 0.0911 0.0903 0.0345 0.0153
Elemental
Carbon
DEP Surrogate 1046 ND 760 10.0 1036 164 2016 115 616 18.6 650 285

a
ND: Not determined

b
NA: Not available

46
While the OSHA PEL concentration threshold thus seems excessively high based on these
calculated cancer risks, it should be noted that this prima facie discrepancy arises because the
PEL pertains to acute exposures (< 8 hrs/day), while the calculated ELCR is based on a 70-year
lifetime of daily exposures. To put the measured chromium (VI) concentrations in perspective, as
of 2010, the average ambient chromium (VI) concentrations in California were found to be
approximately 0.04-0.06 ng/m
3
(Propper et al., 2015), which is 2-3 orders of magnitude lower
than the concentrations found within the subway environments.
The highest concentrations of total PAHs with an associated health risk (0.940 ± 0.346
ng/m
3
) were found along the I-710 freeway, which was also the only sampling route with a
detectable concentration of BaP (0.0886 ± 0.0479 ng/m
3
). Higher PAH concentrations observed
along the I-710 freeway result from a higher percentage of HDVs, which emit more PAHs than
do LDVs (Ning et al., 2008; Phuleria et al., 2006). Additionally, a higher proportion of HDVs,
which are primarily diesel-fueled, on the I-710 freeway, resulted in a higher concentration of
DEP, as indexed by EC. The concentration of EC measured along the I-710 was 2016 ± 115
ng/m
3
, as compared to 1036 ± 164 ng/m
3
along the I-110 freeway.
3.3.2 Cancer and Non-Cancer Health Risks Along Commuter Routes
Figures 3.2a and 3.2b present the cancer risk (ELCR) posed by individual metal and PAH
species, respectively, of particulate matter collected at the five different sampling locations. As
can be seen in the data presented in Figure 3.2a, chromium led to the greatest cancer risk of all
metals (ELCR = 4.1 x 10
-5
at the METRO red line), by at least one order of magnitude, at all
sampling locations. Elemental Carbon (EC), as a surrogate for DEP, also presented a substantial
contribution to cancer risk (METRO red line ELCR = 2.7 x 10
-7
).

47

Figure 3.2a: Excess lifetime cancer risk for metals and diesel exhaust particulate (DEP)

Figure 3.2b: Excess lifetime cancer risk for polycyclic aromatic hydrocarbons (PAHs)

1.0E-10
1.0E-09
1.0E-08
1.0E-07
1.0E-06
1.0E-05
1.0E-04
1.0E-03
As Co Cd Cr Pb Ni DEP (EC)
Gold Line Red Line I-110 I-710 Wilshire/Sunset PIU
1.0E-11
1.0E-10
1.0E-09
1.0E-08
Gold Line Red Line I-110 I-710 Wilshire/Sunset PIU

48

Figure 3.2b reveals that among the PAHs, BaP poses the greatest cancer risk (ELCR = 1.2 x
10
-9
) though it was only detected along the I-710 freeway. While the cancer risk of BaP is not
trivial, it makes an insignificant contribution to overall risk in an environment (e.g. a subway
system) where emissions of metallic carcinogens such as hexavalent chromium dominate.
Of the metals present in both subway and roadway environments, hexavalent chromium, with
an exceptionally high cancer potency factor of 42.0 (USEPA) or 510 (OEHHA) (mg/kg-day)
-1
, is
the largest contributor to overall cancer risk. Thus, the high concentrations of airborne metals
measured in the subway setting (METRO red line) of the current study, as well as in the Chillrud
et al. (2004) study of the New York City subway system, should be of special concern to
commuters.
Figure 3.3: Non-cancer risk (hazard quotient)

1.0E-05
1.0E-04
1.0E-03
1.0E-02
1.0E-01
1.0E+00
Al As Cd Cr Ni Pb Mn
Gold Line Red Line I-110 I-710 Wilshire/Sunset PIU

49

Figure 3.3 presents the chronic non-cancer health hazard risk (HQ) posed by relevant
transition metals. The greatest non-cancer risk along the METRO red line was due to Cd (HQ =
6.0 x 10
-3
), Cr (HQ = 2.8 x 10
-3
), Ni (HQ = 1.0 x 10
-2
), and Mn (HQ = 2.1 x 10
-2
), while
generally, across all sampling locations, Ni and Mn produced the greatest health hazards
compared to other metals, as can be seen in Figure 3.3. Note that an RfC value was available to
calculate the HQ for only one PAH (BaP), therefore it is not included with the metals HQ results
depicted in Figure 3.3.
Figures 3.4a and 3.4b present the Total ELCR (cancer risk) and HQ (non-cancer risk) values,
respectively, at each of the various sampling sites, calculated as the sum of individual ELCR and
HQ values of all relevant metals and PAHs present at each site. Total values were calculated
based on the CP and RfC/REL values provide by the USEPA and OEHHA, however if only one
value was available for any individual metal or PAH, it was used in both calculations. A
depiction of the Maximum ELCR or HQ at each site, along with the total values calculated using
USEPA and OEHHA factors alone, is also included in Figures 3.4a and 3.4b based on using the
higher CP or RfC/REL values.
Figure 3.4a: Excess lifetime cancer risk - totals by site
1.0E-10
1.0E-09
1.0E-08
1.0E-07
1.0E-06
1.0E-05
1.0E-04
1.0E-03
1.0E-02
1.0E-01
1.0E+00
Gold Line Red Line I-110 I-710 Wilshire/Sunset PIU
ELCR (EPA) ELCR (OEHHA) ELCR Max

50

Figure 3.4b: Non-cancer risk (hazard quotient) - totals by site

While the results of risk calculations in Kam et al. (2013) indicated that traveling on the I-
710 freeway posed the greatest cancer risk to commuters due to PAH-laden roadway PM, the
current analysis indicates that commuters riding the METRO red line train in fact experience a
greater cumulative cancer risk (4.2 x 10
-5
) due to the presence of carcinogenic metals in the
airborne PM to which they are exposed. METRO red line travelers are also subjected to the
greatest cumulative non-cancer chronic health risk (4.1 x 10
-2
), though non-cancer risk values
determined at all sites were well below the accepted safety threshold of 1.0.
The maximum calculated ELCRs associated with the other commuter routes examined were
all lower than that of the METRO red line, but did not differ significantly from each other. The
cancer risk of riding the METRO gold line (4.2 x 10
-6
) was comparable to that of driving on the
I-110 (4.1 x 10
-6
) and I-710 (3.8 x 10
-6
) freeways, as well as the risk inherent in utilizing the
surface streets Wilshire and Sunset (3.2 x 10
-6
). Additionally, the non-cancer risk of riding the
1.0E-03
1.0E-02
1.0E-01
1.0E+00
Gold Line Red Line I-110 I-710 Wilshire/Sunset PIU
HQ (EPA) HQ (OEHHA) HQ Max

51

METRO gold line was the second lowest of the five commuting options (2.9 x 10
-3
), a miniscule
amount above the I-110 value (2.3 x 10
-3
). It would thus seem that freeway commuting is a safer
option for commuters, by a small margin. However, it should be kept in mind that other hazards
exist on roadways and freeways including non-particulate air pollution (e.g. carbon monoxide,
nitrogen oxides, and gas-phase volatile organic compounds), as well as the immediate and
significant risk of vehicle collisions, which may outweigh the slight cancer risk advantage.
Based on these data, we can conclude that the best option for commuters, provided there are
routes available to bring them near their workplace, is to use above-ground light-rail transit when
possible. Greater ventilation provides for lower concentrations of both metals and PAHs, and the
use of freeways or surface streets is obviated along with the danger of motor vehicle collisions,
resulting in the least health risk overall.
3.4 Summary and Conclusions
Commuters in Los Angeles, whether traveling by light rail, subway, or motor vehicle, are
exposed to particulate matter containing significant concentrations of PAHs and transition metals
on a daily basis. In this comparative study of the health risks, both cancerous and non-cancerous,
of various modes of transportation, both roadway- and railway-based, we determined that
commuters riding the METRO red line experience the most significant health risks, and that
these risks, both cancer and non-cancer, are driven largely by the hexavalent chromium content
of the PM. While freeway commuters are not risk-free, due to PAH exposures as well as non-
pollution related hazards, there is lower exposure to carcinogenic transition metals. Above-
ground light-rail trains offer the best of both worlds, in that riders are removed from much of the
traffic-generated PAHs which plague freeways, while the open air and greater circulation at
railway platforms mitigate the effects of exposure to airborne metals associated with railways.

52

Chapter 4

Oxidative Potential of Ambient Particulate Matter in Beirut
During Saharan and Arabian Dust Events

In this study, we examine the oxidative potential of airborne particulate matter (PM) in Beirut,
Lebanon, as influenced by dust events originating in the Sahara and Arabian deserts. Segregated
fine (< 2.5 µm) and coarse (2.5-10 µm) PM samples collected during dust events, as well as
during non-dust periods, were analyzed for chemical composition, and an in vitro alveolar
macrophage (AM) assay was performed to determine the oxidative potential of both types of
samples. We performed Spearman rank-order correlation analysis between individual chemical
components and the oxidative potential of PM to examine the impact of the changes in PM
chemical composition due to the occurrence of dust events on overall PM oxidative potential.
Our findings revealed that the oxidative potential of Beirut’s urban PM during non-dust periods
was much higher than during dust episodes for fine PM. Our findings also indicated that tracers
of tailpipe emissions (i.e., elemental (EC) and organic carbon (OC)), non-tailpipe emissions (i.e.,
heavy metals including Cu, Zn, As, Cd, and Pb), and secondary organic aerosols (SOA) (i.e.,
water-soluble organic carbon, WSOC) are significantly associated with the oxidative potential of
PM during dust days and non-dust periods. However, the contribution of desert dust aerosols to
Beirut’s indigenous PM composition did not exacerbate its oxidative potential, as indicated by
the negative correlations between the oxidative potential of PM and the concentrations of crustal
elements that were enriched during the dust days. This suggests that aerosols generated during
Saharan and Arabian dust events pose no additional health risk to the population due to PM-
triggered reactive oxygen species formation. These results significantly contribute to our
understanding of the effects of desert dust aerosols on the composition and oxidative potential of
PM in several countries throughout the entire Middle East region that are impacted by dust
events in the Sahara and Arabian deserts.
This chapter is based on the following publication:
Lovett, C., Sowlat, M. H., Saliba, N. A., Shihadeh, A. L., & Sioutas, C. (2018). Oxidative potential of
ambient particulate matter in Beirut during Saharan and Arabian dust events. Atmospheric
Environment, 188, 34-42. DOI: 10.1016/j.atmosenv.2018.06.016

53

4.1 Introduction
Beirut, Lebanon, a major coastal city on the eastern edge of the Mediterranean Sea, is subject
to particulate remnants of dust events originating in both the Sahara Desert of North Africa, as
well as the Arabian Desert of the Arabian Peninsula. When dust events occur, the resulting
airborne particulate matter (PM) from the Sahara travels eastward, making its way over the
Mediterranean Sea to Beirut (Athanasopoulou et al., 2016). Aerosols from dust events in the
Arabian Desert, however, migrate westward through the urban atmospheres of Saudi Arabia,
Jordan and eastern Lebanon before joining with the indigenous Beirut particulate matter (PM)
above the city (Jaafar et al., 2014). As a large urban center representative of several large
middle-eastern cities throughout the region, particulate air pollution in the urban atmosphere
above Beirut arises primarily from vehicle emissions (tailpipe and non-tailpipe), marine
emissions and port activity, construction projects, sea salt, and airborne dust composed of crustal
material (CM) and metals (Borgie et al., 2016; Daher et al., 2013, 2014; Saliba et al., 2006, 2010;
Saliba & Massoud, 2010; Kouyoumdjian et al., 2006; Giannadaki et al., 2014).
Particulate matter (PM), especially fine PM (less than 2.5 μm in diameter, or PM2.5), has been
associated with several adverse effects on human health, including asthma, lung cancer, coronary
heart disease, and heart failure (Li et al., 2003a; Dockery et al., 1993; Shah et al., 2013; Kim et
al., 2013; Delfino et al., 2005; Samet et al., 2000; Dominici et al., 2006), as well as central
nervous system (CNS) dysfunction resulting from neuroinflammation and subsequently induced
cytokine production (Davis et al., 2013; Levesque et al., 2011; MohanKumar et al., 2008; Cheng
et al., 2016a, 2016b). These adverse health effects resulting from PM exposure are largely
mediated by a cellular inflammatory response that includes production of reactive oxygen
species (ROS), a cellular defense mechanism primarily occurring in epithelial cells of the lungs

54

as well as in various neurons and glia of the brain (Li et al., 2003b, 2009a; Prahalad, 1999).
Oxidative potential, a measure of the potential for PM to induce the formation of ROS and other
oxidative species intercellularly, has been linked to specific PM components, some more toxic
than others. These PM species and their associated oxidative potential have been attributed to
various sources of particulate emissions in several studies (Decesari et al., 2017; Argyropoulos et
al., 2016; Mousavi et al, 2018a; Shirmohammadi et al., 2018).
In the current study, we examine the influence of desert dust episodes on the oxidative
potential of PM indigenous to Beirut, Lebanon, and correlate this redox activity to specific PM
species. When dust events of both Saharan and Arabian origin occur, they contribute
significantly to the aerosol composition in Beirut’s urban atmosphere. The impact of these
alterations to PM composition on health effects, as mediated by the oxidative stress and
inflammatory response of cells during exposure, has not previously been extensively studied.
Using the in vitro alveolar macrophage (AM) assay, we first measured the redox activity of PM
samples collected during dust events and non-dust periods. This assay involves exposing alveolar
macrophage cells derived from the epithelial lining of the rat lung to PM samples and
quantifying the cellular formation of oxidative species during the inflammatory response
(Rosenkranz et al., 1992; Landreman et al., 2008; Shafer et al., 2010). Chemical analysis of the
components of the PM samples collected during dust events and non-dust periods was also
performed, and the relationship between these results and the oxidative potential of the PM
samples was examined using Spearman rank-order correlation analysis.
The influence of dust events on particulate matter toxicity is a topic of great interest for the
entire Middle Eastern region, extending far beyond the local confines of Beirut, and is heavily
debated within the scientific community. Residents of several semi-arid and arid regions of the

55

Middle East have argued that the recommended PM significance thresholds listed in the World
Health Organization’s Air Quality Guidelines (WHO, 2006) cannot be directly applied to their
regions because there have been no carefully designed studies evaluating the toxicity of these
particles as affected by dust events. Our study is one of the first to examine changes to PM
composition and toxicity under these conditions.
4.2 Methodology
4.2.1 Sampling Location and Schedule
PM sampling was done on the roof of the 20-meter high Chemistry building at the American
University of Beirut (AUB) during the summer and fall of 2012. The university is located in the
northwest region of Beirut (33°90’N, 35°50’E) in close proximity to commercial areas and high-
volume roadways, thus we may assume the PM samples collected at this location are highly
representative of the city’s urban atmosphere (Baalbaki et al., 2013; Daher et al., 2013).
Size segregated PM samples were collected using three Sioutas Personal Cascade Impactor
Samplers, or PCISs (SKC Inc., Eighty-Four, PA, USA; Misra, et al., 2002; Singh, et al., 2003),
operating in parallel, each preceded by a 10 μm cut-point impactor (Chemcomb Model 3500
Speciation Sampling Cartridge) and operating at a flow rate of 9 lpm. Each PM sample was
collected over a 24-hour time period. Separate coarse (PM10-2.5), accumulation mode (PM2.5-0.25)
and ultrafine (PM0.25) particle fractions were collected; however, in the current study we combine
the results of accumulation mode and ultrafine PM analyses into one size fraction, i.e. PM2.5.
Teflon (PTFE) filters (Pall Life Sciences, Ann Arbor, MI) were utilized in two of the PCISs
and were subsequently analyzed for PM mass, inorganic secondary ions and total metals. The
third PCIS utilized quartz microfiber filters (Whatman International Ltd., Maidstone, England)

56

and analysis of these samples for water-soluble organic carbon (WSOC) as well as organic and
elemental carbon (OC/EC) was subsequently performed.
Ten PM samples segregated into size fractions (6 fine, 4 coarse) were collected during dust
event days, and nine PM samples (5 fine, 4 coarse) were collected during non-dust days. While
this might appear to be a rather limited sample size, it should be noted that dust storms are
infrequent events, therefore by its nature, this type of research is one of opportunity. Dust storm
episodes are not a daily or weekly occurrence, even in the Middle East, and during such events
conditions prevail that cannot be replicated in a laboratory. Therefore, we collected samples
based on the occurrence of these events within a reasonable timeframe.
Dust days were identified using the Hybrid Single Particle Lagrangian Integrated Trajectory
Model (HYSPLIT) model (Draxler and Rolph, 2013). Confirming evidence of desert dust events
was provided by the BSC-DREAM dust maps website (http://www.bsc.es/ess/bsc-dust-daily-
forecast/). Because aerosols resulting from dust episodes could continue to influence the local
PM concentrations even after an episode ends (Zender et al., 2003), the day an event occurred as
well as the two days following were considered “dust days” for the purposes of this study.
Complete details of the PM sampling methodology and dust event determination procedure are
documented in Dada et al. (2013) and Jaafar et al. (2014). During the campaign, four individual
dust episodes were identified, for which 6 fine and 4 coarse PM samples were collected (Table
4.1). Sampling during dust days extended over the 24-hour average collection time in some
cases.

57

Table 4.1: Sampling dates following dust episodes
Dust Episodes 1 2 3 4
Sampling
Dates
Oct 3-4 Oct 22-24 Oct 31-Nov 2 Nov 2-4 Nov 19-21 Nov 21-23
Episode Type
Arabian
Remnant
Saharan –
Arabian
Arabian + Saharan
Remnant
Saharan - Arabian

4.2.2 Gravimetric and Chemical Analyses
Gravimetric analysis consisted of weighing all filters pre- and post-sampling with a high-
precision microbalance to determine mass loading. Total metals content of the PM samples was
determined by analysis of the Teflon filters using magnetic-sectored Inductively Coupled Plasma
Mass Spectroscopy (HR-ICP-MS Thermo-Finnigan Element 2) after acid extraction (Zhang, et
al., 2008). The extraction utilized a Teflon bomb digestion protocol, using an acid mixture
composed of 1 mL of 16 M nitric acid (HNO3), 0.25 mL of 12 M hydrochloric acid (HCl), and
0.10 mL of hydrofluoric acid (HF) (Herner et al., 2006). The digestion period included a gradual
increase in temperature to 180 °C over 9 minutes and holding the digestion mixture at 180 °C for
an additional 10 minutes, followed by a 1-hour cool-down period. Digestates were then diluted to
15 mL with ultrapure water, and ICP-MS analysis was then conducted (Lough et al., 2005).
Metal recovery rates and reference material information for this analysis are included as a
Supplementary Information (SI) Excel file. Concentrations of inorganic secondary ions in PM
samples were measured by ion chromatography (Model 2020i, Dionex Corp.) performed on high
purity water extractions of the Teflon filters. Analysis of the quartz filters for elemental carbon
(EC), organic carbon (OC) was done using the method of Thermal Evolution/Optical
Transmittance (Birch and Cary, 1996). After water-extraction and filtration (0.22 μm pore size)

58

of the quartz filter samples, WSOC content was determined using a Sievers 900 Total Organic
Carbon Analyzer (Sullivan et al., 2004). Prior to sampling, all quartz filters were prebaked at 550
°C for 12 hours and then packaged in baked aluminum foil for storage.
4.2.3 Determination of PM Oxidative Potential via the Alveolar Macrophage (AM) Assay
The AM assay was used to quantify the oxidative potential of the PM samples. Alveolar
macrophage cells used in this assay are scavenging cells found in vivo in the inner epithelial
lining of the rat lung. For the in vitro assay, the NR8383 immortalized cell line was used. During
the assay, macrophage cells were exposed to PM samples, and the compound 2,7-
dichlorodihydrofluorescein diacetate (DCFH-DA) was used as a fluorescent probe to quantify
the cellular formation of oxidative species. As the non-fluorescent compound DCFH-DA enters
the cell, it is de-acetylated by cellular enzymes to produce 2,7-dichlorodihydrofluorescein
(DCFH), also a non-fluorescent compound. DCFH is then oxidized by any reactive species
generated during the cellular response to PM exposure, forming the highly fluorescent and
detectable 2,7-dichlorofluorescein (DCF). Finally, DCF concentration is quantified via a
spectrophotometric microplate reader (504 nm excitation and 529 nm emission) in fluorescence
units per mass of PM (FU/μg-PM), and serves as an index of reactive species formation
(Rosenkranz et al., 1992; Landreman et al., 2008; Shafer et al., 2010). Fluorescence
measurements are done on a dilution series for each sample extract, thus establishing a
calibration curve and linear dose-response region.
Zymosan is used in the macrophage assay as a positive control to induce a cellular oxidative
response, as it activates membrane-bound toll-like receptors (TLR) of the alveolar macrophages,
thus initializing a reliably strong response. Results of the macrophage assay are reported in
standard Zymosan units to allow data comparisons across different sample batches and

59

experiments, minimizing difference due to variations in instrument sensitivity and cell cultures.
After blank correction, the fluorescence data in units of FU/μg-PM is normalized to the response
of a unit of Zymosan, and reported in units of μg-Zymosan/μg-PM. The mass concentration (μg-
Zymosan/μg-PM) is then multiplied by the ambient PM concentration corresponding to each
analyzed sample to generate standardized volumetric concentrations (μg-Zymosan/m
3
-air), which
are more relevant when discussing real-world population exposures to ambient PM.
4.2.4 Correlational Analysis of Oxidative Potential and PM Species
Bivariate correlation analysis was conducted by calculating Spearman’s rho (non-parametric)
coefficients for the measured air volume-based concentrations (i.e. per m
3
of air) of chemical
species and oxidative potential of PM samples collected during dust and non-dust days. These
correlation coefficients allowed us to identify species known to be tracers of specific sources that
are highly associated with PM oxidative potential. It is noteworthy that in this work, a P-value <
0.05 was considered as statistically significant.
4.3 Results and Discussion
4.3.1 Mass Concentration and Chemical Composition of PM
The mass concentrations (μg/m
3
) of coarse and fine PM fractions collected during dust and
non-dust days are presented in Figure 4.1. As can be seen in the figure, greater PM mass
concentrations were observed during dust days as compared to non-dust days in both PM size
ranges. This is quite in accordance with our expectations, and consistent with earlier findings
reported in the literature, which demonstrate the impact of dust episodes on increasing ambient
PM mass concentrations (e.g., Chirizzi et al., 2017; Shahsavani et al., 2012).

60

Figure 4.1: Mass concentrations (μg/m
3
) - dust vs. non-dust days, coarse and fine PM

(a) Coarse PM

(b) Fine PM

Figures 4.2 and 4.3 present the concentrations of ionic species and carbonaceous species,
respectively, present in coarse and fine PM fractions during dust and non-dust days. When
comparing dust vs. non-dust days, concentrations of Na
+
, Cl
-
, EC, OC, and WSOC are not
0
5
10
15
20
25
30
Dust Non-Dust
Concentration (μg/m
3
)
0
5
10
15
20
25
30
35
40
Dust Non-Dust
Concentration (μg/m
3
)

61

drastically different, and are within the variation indicated by error bars (Figs. 4.2 & 4.3), a
finding also reflected in the data of Jaafar et al. (2014).
Figure 4.2: Mass concentrations (μg/m
3
) of inorganic secondary ions - dust vs. non-dust days, coarse
and fine PM
(a) Coarse PM

(b) Fine PM

0.01
0.10
1.00
10.00
CHLORIDE NITRATE SULFATE SODIUM POTASSIUM
Concentration (µg/m
3
)
Dust Days
Non-Dust Days
0.01
0.10
1.00
10.00
100.00
CHLORIDE NITRATE SULFATE SODIUM AMMONIUM POTASSIUM
Concentration (µg/m
3
)
Dust Days
Non-Dust Days

62

As can be seen in Figure 4.2, the concentrations of Cl
-
and Na
+
(tracers of sea salt aerosol)
were higher in the coarse PM fraction (Fig. 4.2a) than in fine PM (Fig. 4.2b), which is expected
given the nature and size of these particles (Hasheminassab et al., 2014b). Concentrations of the
inorganic secondary ions sulfate, nitrate, and ammonium (tracers of ammonium nitrate and
ammonium sulfate), however, were higher in the fine PM size fraction, and in fact no ammonium
was detected in the coarse fraction. This is most likely due to the secondary nature of these
particles, which are preferentially partitioned in the accumulation mode (Daher et al., 2013,
2014). During non-dust days, concentrations of all inorganic ions present in fine PM were higher
than on dust days, in agreement with previous research indicating that the background aerosol in
the Mediterranean region is high in WSOC as well as in inorganic secondary ions (SI) content
(Malaguti et al., 2015; Nicolas et al., 2009), and these species would be diluted by the additional
crustal elements present during dust days.
Figure 4.3: Mass concentrations (μg/m
3
) of carbonaceous species - dust vs. non-dust days, coarse and
fine PM
(a) Coarse PM

0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
OC EC WSOC
Concentration (µg/m
3
)
Dust Days
Non-Dust Days

63

(b) Fine PM

As shown in Figure 4.3, the concentrations of EC (tracer of vehicular emissions), WSOC
(tracer of secondary organic aerosol (SOA) and biomass burning), and OC (from traffic, SOA,
and biomass burning) were much higher in fine PM (Fig. 4.3b) than coarse PM (Fig. 4.3a). We
expect to observe higher EC concentrations in fine PM (especially in the ultrafine range) than in
coarse PM. OC, whether in the form of primary organic carbon (POC), that comes from traffic
emissions and biomass burning, or in the form of secondary organic carbon (SOC), is a PM
species having higher concentrations in the accumulation mode, or fine PM, than in the coarse
PM range, which is in accordance with our results. The same applies to water soluble organic
carbon (WSOC) which is mostly associated with secondary organic carbon and to a lesser extent,
in the Beirut area, with biomass burning (Daher et al., 2013, 2014). When comparing the
carbonaceous species composition of fine PM on dust and non-dust days, concentrations of EC,
OC, and WSOC were higher on dust days as compared to non-dust days, although these
differences are within the range of variation indicated by the error bars (Fig. 4.3b). We also
calculated the OC/EC ratios in the fine PM fraction of ambient samples collected during both
0.0
1.0
2.0
3.0
4.0
5.0
6.0
OC EC WSOC
Concentration (µg/m
3
)
Dust Days
Non-Dust Days

64

dust and non-dust days. Our results indicated that the OC/EC ratio did not change significantly
across dust versus non-dust episodes, with corresponding values of 2.25 and 1.93, respectively.
These ratios are in agreement with those previously measured in Beirut (Waked et al., 2013,
2014).
Table 4.2: Coarse and fine PM metals content during dust and non-dust episodes (mean ± SD)
Compound Dust Days Non-Dust Days
Coarse Fine Coarse Fine
Total Metals (ng/m
3
)

Mg 225 (80.4) 85.3 (35.9) 209 (167) 52.9 (29.5)
Al 366 (99.5) 190 (89.2) 390 (380) 77.5 (44.1)
K 120 (40.3) 168 (78.5) 89.9 (53.3) 148 (51.6)
Ca 1419 (560) 269 (105) 1084 (639) 223 (153)
Ba 8.78 (1.25) 4.20 (1.56) 4.56 (2.50) 3.14 (1.95)
V 2.27 (0.74) 16.2 (9.46) 0.79 (0.44) 11.2 (5.34)
Cr 1.12 (0.15) 0.37 (0.25) 0.57 (0.46) 0.091 (0.078)
Mn 5.40 (1.37) 4.66 (1.17) 3.11 (1.84) 4.32 (1.42)
Fe 375 (72.7) 215 (64.3) 200 (107) 116 (59.5)
Ni
0.63 (0.58) 4.85 (3.13) 2.42 (4.06) 4.11 (2.28)
Cu 4.37 (0.74) 17.0 (15.9) 20.1 (13.6) 22.0 (17.8)
Zn 14.1 (3.65) 60.4 (42.4) 30.0 (13.7) 35.1 (16.0)
As 0.086

0.38 (0.17) 0.11 (0.089) 0.58 (0.12)
Rb 0.50 (0.29) 0.41 (0.094) 0.18 (0.14) 0.47 (0.25)
Cd 0.025

0.22 (0.12) 0.016

0.19 (0.084)
Pb 1.60 (0.22) 20.9 (12.0) 5.16 (6.40) 12.3 (6.25)

The concentrations of trace elements and metals in the coarse and fine PM fractions on dust
and non-dust days are presented in Table 4.2. The concentrations of crustal elements and species
associated with dust particles, including Mg, Ca, Ba, and Fe (Jaafar et al., 2014), are quite higher
on dust days as compared to the non-dust days in both the coarse and fine PM size fractions,
indicating the enrichment of these species during dust episodes. However, such a trend was not
observed for many other elements that are associated with non-tailpipe vehicular emissions,

65

particularly for coarse PM, including Cu, Zn, Cd, Ni, and Pb (Shirmohammadi et al., 2015), and
in many cases the concentrations of this category of species were even higher during the non-
dust days as compared to the dust days. In addition, the concentrations of crustal elements and
tracers of non-tailpipe traffic emissions were higher in the coarse PM than in the fine PM size
fraction, which is in agreement with previous studies (Sowlat et al., 2016; Wang et al., 2016;
Thorpe et al., 2008). K, on the other hand, which is commonly used as a tracer of biomass
burning (Urban et al., 2012), has a higher concentration in the fine PM size range, due to its
predominantly primary nature as a direct product of combustion (Sanderson et al., 2014;
Hasheminassab et al., 2014a).
4.3.2 PM Oxidative Potential
The oxidative potential of particulate matter, as quantified by the AM assay, may be reported
on either a volumetric (i.e. per m
3
of air volume) or per PM mass basis concentration. When
reporting the mass basis, the intrinsic toxicity of the PM is revealed, while on a volumetric basis,
the extrinsic PM toxicity is indexed. The latter method is more directly applicable to the actual
airborne concentrations of PM to which populations are exposed. Therefore, we present and
discuss the per-volume oxidative potential of the PM samples. The volume-based oxidative
potential concentrations were standardized to Zymosan, a positive control that induces a reliably
strong inflammatory response in macrophage cells, and results are reported in units of µg-
Zymosan/m
3
air.
PM oxidative potential values determined for samples collected during dust and non-dust
days are presented in Figure 4.4. As can be seen in the figure, the oxidative potential of coarse
PM was found to be slightly higher during dust days, as compared to the non-dust days.
However, the oxidative potential of fine PM was observed to be drastically higher during non-

66

dust days (720 ± 275 μg-Zymosan/m
3
), as compared to that of fine PM collected during dust
days (280 ± 198 μg-Zymosan/m
3
). This result may be due to the additional dust aerosols present
in the urban atmosphere during storms diluting the concentrations of toxic PM species that are
normally prevalent on non-dust days.
Figure 4.4: PM Oxidative potential (μg-Zymosan/m
3
) - dust vs. non-dust days, coarse and fine PM
(a) Coarse PM

(b) Fine PM
0
200
400
600
800
1000
1200
Dust Non-Dust
μg-Zymosan/m
3
0
5
10
15
20
25
Dust Non-Dust
μg-Zymosan/m
3

67

Chirizzi et al. (2017) also examined the oxidative potential of ambient PM2.5 from dust and
non-dust sources. These authors used a different assay to assess the redox properties of PM,
called the dithiothreitol (DTT) assay (Rattanavaraha et al., 2011; Li et al., 2009b; Verma et al.,
2009). This is a cell-free molecular assay that assesses a PM sample’s oxidative potential by
quantifying the transfer of electrons from DTT to oxygen, which provides an index of oxidative
stress. The DTT redox reaction is similar to the naturally-occurring cellular redox reaction
involving nicotinamide adenine dinucleotide phosphate (NADPH) and oxygen. The rate at which
DTT is consumed during the electron transfer process is measured under standard conditions,
and provides an index of the of the redox-active species concentration in a PM sample. Thus, the
DTT assay is different than the cellular macrophage assay used in our study to determine
oxidative potential.
Several studies have used the DTT assay to measure the oxidative potential of PM as an
index of toxicity and health risk, and many different species have been implicated in the redox
activity of PM. In studies of ambient ultrafine and sub-micron PM (Charrier et al., 2015), as well
as PM2.5 (Charrier et al., 2012), fractions collected at urban and rural sites, the majority of
measured DTT activity has been attributed to transition metals, especially Cu and Mn, as well as
quinones. Samake et al. (2017) found that bioaerosols, specifically fungal spores, exhibit
oxidative potential levels similar to those of metals and quinones. As mentioned above, and of
relevance to the current study, in an examination of PM composition and oxidative potential
during Saharan dust events, Chirizzi et al. (2017) found that the DTT activity of the high carbon
group, which represents combustion-related PM, was more than two times greater than that of
the “Saharan dust outbreak (SDO)” samples, which are equivalent to our “dust days” samples.
This is quite consistent with our observations, reinforcing the finding that for fine PM, the

68

oxidative potential of airborne PM is much higher during non-dust periods than during dust
periods.
Additionally, comparing the oxidative potential of coarse PM (Fig. 4.4a) to fine PM (Fig.
4.4b), we can see there is at least an order of magnitude difference, with the bulk of oxidative
potential due to fine PM. These results are thus in agreement with previous findings that desert
dust aerosols, with low oxidative potential, exist largely in the coarse PM fraction, while traffic-
generated PM emissions including SOA/WSOC, which elicit a greater oxidative stress response
in cells, are primarily fine PM (Kouyoumdjian et al., 2006; Shirmohammadi et al., 2015; Saffari
et al., 2014).
4.3.3 Bivariate Correlations Between Individual Species and Oxidative Potential
The Spearman’s rank correlation coefficients between oxidative potential and ambient
concentrations of individual marker species are presented in Table 4.3 for dust and non-dust
days, as well as for the combined dataset. Statistically significant correlations (p < 0.05) are
presented in bold. As can be seen in the table, oxidative potential of PM was significantly
associated with markers of tailpipe vehicular emissions (i.e., EC and OC) (Schauer et al., 2003),
secondary inorganic aerosol (i.e., SO4
2-
and NH4
+
), secondary organic aerosol (SOA) (i.e.,
WSOC) (Ding et al., 2008; Fine et al., 2004), and non-tailpipe emissions (i.e., Ni, Cu, Zn, As, V,
Cd, and Pb) (Harrison et al., 2012; Sanderson et al., 2014). Other than secondary inorganic ions,
these marker species have been statistically significantly correlated with the oxidative potential
of PM in previous studies (Argyropoulos et al., 2016; Decesari et al., 2017; Shirmohammadi et
al., 2015). There is no biological evidence to support toxic properties of inorganic ions, so we
attribute their association with oxidative potential to their collinearity with WSOC, since all of
these species are products of photochemical reactions in the atmosphere (Saffari et al., 2015).

69

Table 4.3: Spearman’s Rho correlation coefficients. Values indicate correlations between
concentrations of chemical species (µg/m
3
) and oxidative potential (µg-Zymosan/m
3
) of PM during
dust days (n = 10) and non-dust days (n = 9). Statistically significant correlations (p ≤ 0.05) are in
bold.

Species
Combined
dataset
Dust-
days
Non-dust
days
OC 0.80 0.96 0.86
EC 0.79 0.92 0.81
WSOC 0.72 0.83 0.86
SO 4
2-
0.74 0.65 0.87
NH 4
+
0.79 0.86 0.30
S 0.90 0.82 0.97
Ba -0.34 -0.59 0.10
Mg -0.53 -0.83 -0.20
Al -0.52 -0.60 -0.27
Fe -0.37 -0.64 -0.02
Ca -0.62 -0.83 -0.42
V 0.84 0.95 0.95
Ni 0.68 0.89 0.73
Cu 0.41 0.84 0.05
Zn 0.40 0.90 0.22
As 0.91 0.82 0.98
Cd 0.79 0.92 0.82
Pb 0.54 0.93 0.30

The results of the Spearman’s correlation analysis between these species and WSOC
indicated R values as high as 0.73 for sulfate and 0.78 for ammonium, both of which were
statistically significant (p < 0.05). It is noteworthy that most of the PM compounds associated
with oxidative potential during non-dust days were also found to correlate highly during dust
days, once again underscoring the importance of tailpipe and non-tailpipe emissions, as well as
photochemistry on the overall PM toxicity. In contrast, in the case of tracers associated with soil
dust, including Mg, Ca, Ba, and Fe, we clearly observed negative correlations, which are in most

70

cases statistically significant. These species are enriched during the dust days, as indicated in
Section 4.3.1 and Table 4.2, emphasizing the finding that dust events do not significantly
contribute to oxidative potential of ambient PM.
4.4 Summary and Conclusions
In this study, we examined the effects of aerosols arising from dust events in the Sahara and
Arabian deserts on the composition and oxidative potential of airborne PM in Beirut, Lebanon.
Utilizing bivariate correlation analysis, we identified marker species of ambient PM that were
highly associated with PM oxidative potential observed during both dust days and non-dust
periods. The major marker species that were found to be associated with the oxidative potential
of PM collected during dust days and non-dust periods included EC and OC (tracers of tailpipe
emissions), WSOC (tracer of SOA), and heavy metals such as Ni, Cu, Zn, As, V, Cd, and Pb
(tracers of non-tailpipe emissions), which is typical of atmospheric composition in dense urban
areas. However, the major marker species associated with soil dust, whose concentrations were
enriched during dust days, were found to be negatively correlated with the oxidative potential of
PM. Therefore, we can conclude that dust events contribute minimally to health impacts caused
by the oxidative potential of airborne particulate matter in Beirut.
By performing this study of PM oxidative potential during dust vs. non-dust days, we sought
to gain a better understanding of Saharan and Arabian dust events, as well as the effects of the
resulting dust aerosols on the chemical composition and oxidative potential of particulate
pollution in the urban atmosphere of Beirut, as a representative large Middle Eastern city.
Ultimately, these results will contribute to a more comprehensive understanding of the complex
interactions between urban PM and such natural desert phenomena as well as the subsequent
influence of such mixed atmospheric environments on human health as mediated by the

71

oxidative stress induced by these particles. Such an understanding is crucial to many large urban
cities in the entire Middle East region as well as other geographically similar regions
experiencing dust events that alter the composition of their indigenous urban PM. The
conclusions to be drawn from this paper may ultimately even influence the decisions of the
policy-makers that will impact many urban populations throughout the Middle East.

72

Chapter 5

Conclusions

The results of the dissertation research presented herein will ultimately contribute to a more
comprehensive picture of the complexity of urban atmospheric particulate matter in megacities
such as Los Angeles, California, as well as the health risks and mechanisms of toxicity
associated with this PM on both the macroscopic and microscopic scales.
Distinctions between primary PM and its secondary products of photochemical oxidation, as
well as their specific health effects, must be carefully examined to allow for a cohesive
understanding of the varied and dynamic nature of urban PM toxicity to emerge. The complex
interactions between PM sources, species, and cellular mechanisms of oxidative stress and
inflammation that drive many of its adverse health effects must be better understood in order to
inform policy and law makers charged with protecting the public from the pollutant byproducts
of the modern society that we enjoy. The research presented in Chapter 2, examining diurnal
changes in PM composition and the cellular oxidative stress response, will help in accomplishing
these aims.
A macroscopic examination of the long-term cancer and non-cancer health risks faced by
residents of large cities, including the risks posed by commuting several hours per year in non-
ideal conditions often involving exposures to high concentrations of PM and other airborne
pollutants, is also vital in providing a comprehensive assessment of the true costs to one’s health
associated with living in a megacity such as Los Angeles. The research presented in Chapter 3,
examining the chronic health risks faced by commuters in Los Angeles, was motivated by such
concerns. The results are illuminating and will hopefully lead to further regulation and mitigation
measures to reduce PM exposures along underground subway commuter routes.

73

Finally, urban cities do not exist in a vacuum. We must consider the influences of the
surrounding geography and the common meteorological conditions within which large cities
such as Los Angeles and Beirut are embedded, and identify potential changes in PM source
profiles, species, and resulting toxicity. The research presented in Chapter 4, examining the
influence of dust storms on urban PM toxicity in the representative city of Beirut, Lebanon, was
conducted with this goal in mind. Additionally, based on geographic location and preponderance
of vegetation, PM deriving from both anthropogenic and biogenic sources may be present in
different amounts, as well as in different oxidation states depending time of year and hours of
daylight, and it was the purpose of the oxidative flow reactor research presented in Appendix A
to explore some of these differences.
Taken together, the studies presented in this dissertation provide a valuable addition to the
canon of knowledge that has been accumulating over several decades regarding the ubiquitous
chemical pollutants that result from the widespread industrial processes and vehicular transport
that define urban life in the modern world. As our understanding of the processes involved in the
production and transformation of particulate matter, as well as its specific mechanisms of
toxicity, continues to evolve, we will ideally be able to better prevent and control these emissions
through more refined regulatory efforts, better designed industrial and combustion processes, and
more advanced control technologies, with the ultimate goal of protecting the environment we all
enjoy and improving human health.

74

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Appendix A

Oxidative Potential of Primary (POA) and Secondary (SOA) Organic
Aerosols Derived from α-Pinene and Gasoline Engine Exhaust Precursors

Organic aerosols in the urban atmosphere are thought to play an important part in the etiology of
respiratory and cardiovascular diseases, largely through systemic inflammation and oxidative
stress. Secondary organic aerosols (SOA) represent a major fraction of ambient organic aerosols,
however their relative contribution to the inhalation burden of inflammatory and oxidative agents
is rather poorly characterized. In this reaction chamber study, we compared the chemical
composition (EC/OC, metals, WSOC, organics), particle size distributions, and oxidative stress
potentials (assessed by an alveolar macrophage assay) of aerosols from raw and oxidized
gasoline engine exhaust, and pure and oxidized α-pinene. The SOA was generated using an
oxidation flow reactor, fed either by pure, aerosolized α-pinene (diluted 50:1) or by gasoline
engine exhaust (diluted 250:1), chosen as representative emissions of biogenic and
anthropogenic sources, respectively. The flow reactor was operated at 22 °C and 60% relative
humidity (RH), utilizing ultraviolet (UV) lamps to achieve an equivalent atmospheric aging
process of several days. Comparisons of oxidative potential between the various aerosols were
made, and contrasted to previously reported data for ambient air. Anthropogenic SOA was found
to produce the greatest oxidative response compared to biogenic (α-pinene) SOA, thus
emphasizing the importance of monitoring and controlling anthropogenic emissions in the urban
atmosphere. However, we must also take into consideration spatial and temporal differences in
SOA composition, as the local concentrations of various species making significant contributions
to the oxidative potential of ambient PM may vary widely depending on the given region or time
of year.
Partial results of the research presented in this chapter have been published in the following
journal:
Lovett, C., Baasiri, M., Atwi, K., Sowlat, M. H., Shirmohammadi, F., Shihadeh, A. L., & Sioutas, C.
(2018). Comparison of the oxidative potential of primary (POA) and secondary (SOA) organic
aerosols derived from α-pinene and gasoline engine exhaust precursors. F1000 Research, 7, 1031.
DOI: 10.12688/f1000research.15445.1.

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A.1 Introduction
Airborne particulate matter (PM) consists of primary emissions from anthropogenic sources,
including products of fossil fuel combustion, road dust, and industrial emissions from
manufacturing and chemical facilities, as well as from biogenic sources within terrestrial
ecosystems, which generate aerosols such as pollen, spores, suspended crustal elements, sea salt,
viruses, microorganisms, and plant-derived hydrocarbons, including isoprene, sesquiterpenes,
and monoterpenes such as α-pinene (Alfarra et al., 2006; Mauderly & Chow, 2008; Després et
al., 2012; Hallquist et al., 2009).
Once emitted, both anthropogenic and biogenic primary particulate, including primary
organic aerosols (POA), undergo a myriad of photochemical oxidation reactions in the
atmosphere as they mix and interact with other particulate and gaseous pollutants such as
nitrogen oxides (NOx), ozone (O3), volatile organic compounds (VOCs), and various oxygen
radicals. These photo-oxidation reactions are catalyzed by ultraviolet (UV) radiation emanating
from the sun, which facilitates the formation of several intermediary species and semi-volatile
organic compounds in the atmosphere during daylight hours (Forstner et al., 1997; Turpin et al.,
2000; Grosjean & Seinfeld, 1989). This process ultimately results in a multitude of secondary
PM oxidation products, including metal oxides, organic acids, and oxidized organic species
condensed around core particulate nuclei consisting of elemental carbon, metals, and various
other elements (Odum et al., 1996; Hoffmann et al., 1997; Seinfeld & Pandis, 2016). The
products of organic species oxidation are collectively known as secondary organic aerosols
(SOA). While up to 70% of fine particulate matter (PM2.5) in the atmosphere consists of organic
species, the reaction and formation mechanisms of these compounds are the least well
understood (Turpin et al., 2000).

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A large fraction of ambient particulate in the urban environment consists of a mixture of
POA components derived from both anthropogenic PM (e.g. PAHs, hopanes, steranes, and
EC/OC) arising from vehicular and industrial sources, and biogenic PM (e.g. isoprene,
sesquiterpenes, monoterpenes such as α-pinene, alcohols and ketones) released by terrestrial
vegetation, as well as additional SOA components resulting from the photo-oxidation of both
types of POA species (Kamens et al., 1999; Odum et al., 1996; Baltensperger et al., 2005; Griffin
et al., 1999). Up to 90% of urban PM consists of SOA, the majority of which originates from
primary biogenic sources, especially the monoterpene α-pinene, which is one of the largest
components of primary biogenic PM worldwide (Hallquist et al., 2009; Hoffmann et al., 1997;
Kanakidou et al., 2000; Kanakidou et al., 2005; Seinfeld & Pankow, 2003; Hu et al, 2008a), and
thus this compound is highly representative of primary biogenic emissions as a whole.
Ambient particulate matter, especially those particles less than 2.5 µm in diameter (PM2.5),
has been linked to several human health problems, including respiratory distress, asthma, lung
cancer, coronary heart disease, and heart failure (Dockery et al., 1993; Shah et al., 2013; Kim et
al., 2013; Delfino et al., 2005; Samet et al., 2000; Dominici et al., 2006), as well as central
nervous system (CNS) oxidative stress and neuroinflammation, which may result in neural
degeneration and subsequent cognitive deficits (Davis et al., 2013; Levesque et al., 2011;
MohanKumar et al., 2008; Cheng et al., 2016a, 2016b). These effects are mediated largely by the
human body’s inflammatory response to noxious stimuli, including the cellular generation of
reactive oxygen species (ROS) as a defense mechanism against foreign microbes and other
material (Li et al., 2003b; Ray et al., 2012).
Reactive oxygen species, consisting of reactive forms of O2, such as hydroxyl radicals (HO·),
H2O2, and oxygen radicals (e.g. O2·), are compounds produced within eukaryotic cells as a

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response to foreign contaminants in the extracellular matrix. These oxidative species can result in
direct DNA damage (to invading microbes) as well as act as intracellular signaling molecules
activating the upregulation of pro-inflammatory chemokines and cytokines (e.g. interleukins 6
and 8 (IL-6 & IL-8) and tumor necrosis factor alpha (TNFα)) as part of a general cellular
inflammatory response (Li et al., 2003b). The alveolar macrophage (AM) fluorescence assay of
PM oxidative potential, used in the current study, has been utilized extensively to study the
effects of PM in vitro as an index of cellular oxidative stress that is reliably correlated with ROS
formation (Landreman et al., 2008; Shafer et al., 2010).
Much of the research investigating the health effects of PM has focused on primary
emissions, including POA, while detailed studies of the effects of photochemically-aged,
secondary PM are not as common. Primary organic aerosols do contribute significantly to PM
toxicity, but the effect may be exacerbated as POA ages throughout the day and undergoes
photochemical oxidation reactions, often condensing to form secondary organic aerosols.
Several studies have found evidence of both anthropogenic SOA (Decesari et al., 2017;
Argyropoulos et al., 2016; Saffari et al., 2015; Verma et al., 2014, 2015a, 2015b; Weber et al.,
2007) and biogenic SOA (Rohr, 2013; Gaschen et al., 2010; Jang et al., 2006; Baltensperger et
al., 2008) leading to an increase in adverse health effects compared to primary aerosols. SOA has
recently been found to occupy a much more significant fraction of the atmosphere than
previously thought (Jimenez et al., 2009; Volkamer et al., 2006), gaining a better understanding
of its formation mechanisms as well as its specific biological interactions on the cellular level is
key to advancing our knowledge of the biological consequences of PM exposure and enabling us
to more effectively protect human health.

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While existing studies of SOA have revealed a critical role played by cellular ROS activity,
as discussed in, e.g., Jiang et al. (2016), Tuet et al. (2017), and Rattanavaraha et al. (2011), the
exact mechanisms by which SOA induces cellular oxidative stress and exerts its toxicity are
generally not well understood. Even less well studied and understood are the mechanisms by
which biogenic SOA, as compared to anthropogenic SOA, exert their health effects.
Previous studies of biogenic and anthropogenic POA and SOA utilizing flow reactors or
outdoor smog chambers include those of Rattanavaraha et al. (2011) and Tuet et al. (2017).
Rattanavaraha and colleagues allowed fresh diesel exhaust particulate (DEP) to interact with
various mixtures of 11 volatile hydrocarbons, toluene, α-pinene, and NOx in the presence of
sunlight. These authors found that overall the photo-oxidized DEP products produced a greater
DTT response than fresh DEP, and the greatest response was observed when NOx, toluene, and
α-pinene were added to the chamber along with the hydrocarbon mixture at the outset of the
experiment, even when no DEP was initially present. Tuet and colleagues investigated the water-
soluble oxidative potential, as measured by the DTT assay, of POA and SOA associated with
various anthropogenic and biogenic hydrocarbons (e.g. naphthalene, isoprene, α-pinene). Their
results showed that anthropogenic SOA derived from naphthalene produced the greatest
oxidative potential, while biogenic SOA formed from isoprene produced the lowest response.
The results of these two studies provide further evidence that photochemical aging of not only
anthropogenic, but also of biogenic, POA precursors contribute to PM toxicity as indexed by
oxidative potential.
In the current study, we investigate how the chemical composition and oxidative potential (as
indexed by an alveolar macrophage assay) of biogenic and anthropogenic PM change over time
due to photochemical oxidation. To examine each type of POA/SOA individually, from both

102

biogenic and anthropogenic sources, we utilized laboratory reaction chambers to study each type
of PM in isolation, before and after exposure to ultraviolet light, and thus photochemical aging,
collecting PM samples in both the primary (POA) and secondary (photo-oxidized SOA) aerosol
states.
Pure α-pinene was used as a source of primary and secondary biogenic aerosols as it has been
found to be one of the largest components of primary biogenic PM, contributing approximately
25% of annual global emissions on a mass basis according to Seinfeld & Pankow (2003). To
study anthropogenic primary and secondary organic aerosols in the reaction chamber, rather than
isolating a single compound, total gasoline engine emissions were used as the PM source.
Gasoline combustion emissions as a source of POA and subsequently formed SOA are more
representative of the primary PM and products of complex photo-oxidative reactions occurring
between hydrocarbons, nitrogen oxides (NOx) and UV light that are found in the urban
atmosphere (Rattanavaraha et al., 2011).
In the Los Angeles metropolitan area, fossil fuel emissions from vehicular diesel and
gasoline engines account for at least 71% of anthropogenic urban POA, with much of the
remaining POA attributable to cooking emissions, based on the 2010 “California Research at the
Nexus of Air Quality and Climate Change” (CalNex) field study of urban pollutants affecting
ambient air quality and climate change (Hayes et al., 2015; Craven et al., 2013; Ryerson et al.,
2013). However, it has been determined that virtually none of the diesel POA species emitted in
the Los Angeles air basin are transformed into SOA, and thus we may conclude that the majority
of atmospheric SOA results from the oxidation of primary products of gasoline combustion
(Bahreini et al., 2012). The choice to use emissions of a gasoline engine as the representative

103

source of anthropogenic POA and SOA species is thus justified considering the dominance of
vehicular emissions in an urban atmosphere such as that of Los Angeles.
A.2 Methodology
A.2.1 Overview
Anthropogenic PM utilized in this reaction chamber study consisted of gasoline engine
exhaust, while biogenic PM consisted of pure α-pinene in the vapor state. Photochemical
oxidation of the POA to SOA occurred within an oxidation flow reactor (OFR) equipped with a
UV light source. A high humidity environment was maintained, allowing H2O to act as a source
of hydroxyl radicals in UV-catalyzed oxidation reactions during SOA formation. POA and SOA
samples were collected on Teflon and quartz filters downstream of the reactor. Additionally, a
particle size spectrometer at the outlet of the chamber, and parallel to the filters, generated
particle number size distribution data.
A.2.2 POA and SOA Generation
A 64-liter stainless steel oxidation flow reactor operating at 22 °C and 60% RH was used to
generate SOA. The OFR was equipped with a single UV lamp (BHK Analamp, Model No. 82-
9304-03) that produces radiation at 185 and 254 nm, which generates OH radicals from water
vapor. The radicals generated oxidize the precursor species in engine exhaust or α-pinene POA
to form SOA.
Engine exhaust was drawn from a four-stroke single cylinder gasoline engine (Honda
SHX1000, 49cc displacement, 8.0:1 compression ratio) through a rotating disk dilutor (RDD;
Testo Engineering, MD19-3E) operating at a dilution ratio of 50:1. Five liters per minute (lpm)
of diluted engine exhaust was diverted into the reaction chamber, where it was mixed with 20

104

lpm of humidified particle-fee air (combined flow rate of 25 lpm). This resulted in a total
dilution of 250:1 in the anthropogenic PM conditions.
α-pinene vapors were pushed into the OFR by continuous inlet air flowing at a rate of 0.5
lpm that passed through a 250 ml Büchner flask in which a 15-ml glass vial containing α-pinene
was held. The glass vial cap had three small holes to allow for diffusion of α-pinene vapors into
the flask. To allow for a residence time similar to that of the engine exhaust condition, the OFR
was fed 24.5 lpm of humidified, particle-free zero-air. This resulted in a dilution ratio of 50:1 in
the biogenic PM conditions.
A.2.3 α-Pinene Aerosol Sampling Methods
As depicted in Figure A.1, a 64-liter stainless-steel oxygen flow reaction (OFR) chamber was
used to conduct this experiment. For all conditions, aerosol particles were collected downstream
of the reaction chamber. In the SOA conditions, the aerosols were collected while the UV lamp
was on, following a 90-minute residence time. Upstream of the reactor, laboratory zero-air was
passed through an activated carbon denuder and HEPA filter at a flow rate of 25 lpm.
Downstream of the HEPA filter, a fraction of the incoming air stream (0.5 lpm) was diverted to a
pure α-pinene sample suspended in an Erlenmeyer flask, with the remaining 24.5 lpm flow
proceeding through a humidifier to the reaction chamber.

105

Figure A.1: Biogenic PM (α-pinene) sampling setup

A.2.4 Gasoline Engine Exhaust Sampling Methods
As depicted in Figure A.2, a 64-liter stainless-steel oxygen flow reaction chamber was also
used in the anthropogenic PM condition. Upstream of the reactor, laboratory zero air was passed
through an activated carbon denuder, HEPA filter and humidifier at a flow rate of 20 lpm.
Downstream of the HEPA filter and humidifier, an incoming air stream (5 lpm) of diluted (50:1)
gasoline engine emissions joined the zero-air stream and continued to the reaction chamber
(combined flow rate of 25 lpm). The engine was a 4-stroke 1-cylinder gasoline engine (Sawafuji
Electric Co., Ltd., SHX 1000) operating at idling conditions.
Figure A.2: Anthropogenic PM (gasoline engine exhaust) sampling setup

106

A.2.5 Particle Sizing
Particle number size distribution at the oxygen flow reactor outlet was measured during
sampling using a TSI Scanning Mobility Particle Sizer (SMPS; TSI 3082 classifier with TSI
3772 CPC). The SMPS scan time was set to 60 seconds with a 4-second retrace time, 20-second
purge time, and a sheath-to-aerosol ratio of 4:1. This allowed measurement of particles in the
size range of 10-730 nm.
A.2.6 Filter Conditioning
Filters used for sample collection were conditioned prior to sampling. Quartz filters were
baked in a furnace oven at 500 °C for 5 hours. Teflon filters were conditioned for at least 24
hours in an environment controlled at 23 and 46% RH before weighing. Teflon filters were
weighed before and after sampling in order to determine the mass collected and the aerosol mass
concentration. The mass collected on the quartz filters was calculated based on the aerosol
concentration and sampling flow rate through each filter during collection. After sample
collection, the filters were placed in petri dishes lined with baked aluminum and sealed with
Teflon tape. The filters were stored in a refrigerated environment until the time of analysis.
A.2.7 Laboratory Analyses
Composite Teflon filter samples were analyzed for oxidative potential using the alveolar
macrophage fluorescence assay (Landreman et al., 2008; Shafer et al., 2010) and total metals
using magnetic-sectored Inductively Coupled Plasma Mass Spectroscopy (SF-ICPMS) following
acid extraction (Zhang et al., 2008). Quartz filters were analyzed for organics using gas
chromatography/mass spectroscopy (GC/MS) (Mazurek et al., 1987; Schauer et al., 1999) and
EC/OC using Thermal Evolution/Optical Transmittance analysis (Birch and Cary, 1996). Engine
and α-pinene SOA quartz filter samples were also analyzed for total organic carbon (TOC) using

107

a Sievers 900 Total Organic Carbon Analyzer, with identical analysis for water-soluble organic
carbon (WSOC) following water-extraction and filtration (0.22 μm) of the samples (Sullivan et
al., 2004).
The alveolar macrophage (AM) assay was used to determine the oxidative potential of the
various PM samples. Alveolar macrophages are scavenging cells found in vivo in the inner
epithelial lining of the rat lung. For the in vitro assay, an immortalized cell line (NR8383), was
used. During the assay, macrophage cells were exposed to each type of PM sample, with 2,7-
dichlorodihydrofluorescein diacetate (DCFH-DA) used as a fluorescent probe to quantify the
cellular formation of oxidative species. The non-fluorescent DCFH-DA acts by entering the cell,
where it is de-acetylated by cellular enzymes to yield 2,7-dichlorodihydrofluorescein (DCFH),
also non-fluorescent. DCFH is then oxidized by reactive species, generated during the cellular
response to PM exposure, to form the highly fluorescent and detectable 2,7-dichlorofluorescein
(DCF), which can be quantified to index the formation of oxidative species (Landreman et al.,
2008; Shafer et al., 2010).
A.3 Results and Discussion
All laboratory data are presented on a mass-fraction basis (μg/μg-PM), as the per-volume
results (μg/m
3
) are somewhat arbitrary, given that in each experimental condition, the air volume
passed through the reaction chamber underwent adjustments and so sampling data expressed in
these units do not reflect actual per-volume concentrations of PM found in the atmosphere.
However, given the relative constancy of metals content during the process of photochemical
aging, the results of total metals and trace elements analysis are shown on a per volume basis
(μg/m
3
).

108

A.3.1 Particle Size Distributions
Figure A.3 illustrates the average particle number size distribution (PNSD) of engine and α-
pinene SOA. Engine SOA had a number mode of 39,763 particles/cm
3
at a diameter of 61.5 nm,
while α-pinene SOA exhibited a number mode of 8,898 particles/cm
3
at a slightly larger diameter
of 94.7 nm.
Figure A.3: Particle size distribution - engine SOA and α-pinene SOA

Figures A.4a and A.4b show how the PNSDs of engine and α-pinene SOA change over the
course of the photo-oxidation process. The qualitative trend of these SOA particle size
distribution data is similar to the data from the smog chamber study of Baltensperger et al.
(2005), who found that SOA from biogenic (α-pinene) emissions was somewhat larger in size
than the SOA produced from anthropogenic (1,3,5-trimethylbenzene) emissions.

0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
1 10 100 1000
Number Concentration (#/cm
3
)
(α-pinene SOA)
Number Concentration (#/cm
3
)
(Engine SOA)
Particle Diameter (nm)
Engine SOA
a-pinene SOA

109

Figure A.4a: Pre- and post-sampling particle size number distribution - engine POA

Figure A.4b: Pre- and post-sampling particle size number distribution - α-pinene SOA

A.3.2 Elemental/Organic Carbon (EC/OC)
As shown in Figure A.5, engine POA contained the largest mass fractions of both elemental
carbon (EC) and organic carbon (OC), which is driven, in part, by the larger total molecular mass
0
50
100
150
200
250
300
350
400
450
500
1 10 100 1000
Number Concentration (particles/cm3)
Particle Diameter (nm)
Beginning of sampling
End of sampling
0
2000
4000
6000
8000
10000
12000
1 10 100 1000
Number Concentration (particles/cm
3
)
Particle Diameter (nm)
Beginning of sampling
End of sampling

110

of secondary PM after accumulating more oxygenated species over time, thus resulting in
relatively smaller fractions of EC and OC. EC was most abundant in Engine POA (0.086 μg-
EC/μg-PM), with no significant amounts present in either Engine or α-pinene SOA. The OC
mass fractions were much higher in all conditions compared to EC, and the OC fraction of SOA
formed from α-pinene did not differ significantly from that of the SOA formed from primary
engine emissions.
Figure A.5: Mass fractions of EC and OC in engine POA & SOA and α-pinene SOA

A.3.3 Water-Soluble Organic Carbon (WSOC)
As shown in Figure A.6, mass-based WSOC concentrations of α-pinene SOA were higher
than engine SOA, which is consistent with results of organics analysis indicating that α-pinene
SOA contains higher fractions of polar molecules (e.g. organic acids, Figures A.10 & A.11) that
are more water-soluble. As shown in Figure A.12, our results indicate that the oxidative potential
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
EC - Engine
POA
EC - Engine
SOA
EC - a-Pinene
SOA
OC - Engine
POA
OC - Engine
SOA
OC - a-Pinene
SOA
Mass Fraction (µg/µg PM)

111

of engine SOA is higher than that of α-pinene SOA, however given its higher concentration of
WSOC in α-pinene SOA, we would expect the converse based on several prior studies of WSOC
and toxicity (e.g. Wang et al., 2013b; Mousavi et al., 2018b; Decesari et al., 2017;
Shirmohammadi et al., 2018; Daher et al., 2012, 2014; Argyropoulos et al., 2016).
Figure A.6: Mass fractions of WSOC in engine SOA and α-pinene SOA

A.3.4 Total Metals and Trace Elements
Figure A.7 illustrates the volume-based concentrations of metals in the engine POA and SOA
samples. Reporting the volumetric metal concentrations allows us to determine whether and how
the levels of metals change over time, as POA is converted to SOA. As shown in the figure, the
metals concentrations in engine POA and SOA did not differ significantly over time, with the
exceptions of Mn and Sn, which had higher volume-based concentrations in engine SOA. As
0photo-oxidation should not affect the absolute masses of metals contained in POA and SOA,
and the slight difference in the per-volume concentrations can be assumed an artifact of air flow
volume manipulations. Mass fraction data is not included in these results, as metals are neither
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
WSOC (µg/µg-PM)
a-Pinene SOA
Engine SOA

112

created nor destroyed during oxidation, and so their mass fraction will predictably decrease as
more total mass accumulates on the PM as it becomes SOA. Thus, presenting mass fraction data
would not be informative.
Figure A.7: Concentrations of total metals and trace elements in engine SOA and POA

A.3.5 Organic Compounds – PAHs, Hopanes, Steranes, Carboxylic Acids
Results of the organics analysis revealed that engine POA contained higher mass fractions of
PAHs, hopanes and steranes than either engine or α-pinene SOA (Figures A.8 & A.9), which is
as expected given the primary nature of these emissions. A comparison of the two types of SOA
indicated that α-pinene SOA contained some PAHs and engine SOA did not (Figure A.8), while
engine SOA contained hopanes and steranes, while α-pinene SOA did not (Figure A.9). The
PAH results were unusual, as the gasoline engine POA emissions contained a measurable mass
of PAHs, as well as hopanes and steranes, which would lead us to expect some residual PAHs in
the engine SOA.

1.0E-06
1.0E-05
1.0E-04
1.0E-03
1.0E-02
1.0E-01
1.0E+00
1.0E+01
1.0E+02
1.0E+03
1.0E+04
1.0E+05
Li Na Mg Al S Ti V Mn Fe Co Ni Cu Zn As Mo Pd Cd Sn Sb Ba La Pb
Volume Concentration (ng/m
3
)
Engine Exhaust POA Engine Exhaust SOA

113

Figure A.8: Cumulative mass fractions of all PAHs - engine SOA and α-pinene SOA

Figure A.9: Cumulative mass fractions of hopanes & steranes - engine SOA and α-pinene SOA

0.0000
0.0010
0.0020
0.0030
0.0040
0.0050
0.0060
0.0070
0.0080
0.0090
Engine POA a-Pinene SOA Engine SOA
mass fraction (ng/µg PM)
sum low MW sum medium MW sum high MW
0.000
0.005
0.010
0.015
0.020
0.025
0.030
Engine POA a-Pinene SOA Engine SOA
mass fraction (ng/µg PM)
22R-Homohopane 22S-Homohopane
17A(H)-21B(H)-30-Norhopane 17A(H)-21B(H)-Hopane

114

Higher mass fractions of carboxylic acids, however, were seen in both engine and α-pinene
SOA (Figures A.10 & A.11), which is also expected given these are products of POA oxidation
(Forstner et al., 1997; Pandis et al., 1992; Seinfeld & Pandis, 2016). α-Pinene POA was not
analyzed for organic compounds because its sole component was pure, vaporized α-pinene.
Figure A.10: Cumulative mass fractions of organic acids C 15-C 30 - engine SOA & α-pinene SOA

As can be seen in Figures A.10 & A.11, α-pinene SOA contained a higher mass fraction of
organic acids, including large fractions of pinonic acid (0.87 ng/µg-PM), hexadecanoic acid
(0.25 ng/µg-PM), succinic acid (0.15 ng/µg-PM), and phthalic acid (0.099 ng/µg-PM), than
engine SOA. Engine SOA consisted largely of hexadecanoic acid (0.083 ng/µg-PM), glutaric
acid (0.34 ng/µg-PM), succinic acid (0.31 ng/µg-PM), and phthalic acid (0.28 ng/µg-PM). As the
results presented below indicate, compared to hopanes and steranes, the majority of SOA mass is
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
Engine POA a-Pinene SOA Engine SOA
mass fraction (ng/µg PM)
Pentadecanoic Acid Hexadecanoic Acid Heptadecanoic Acid Octadecanoic Acid Nonadecanoic Acid
Pinonic Acid Palmitoleic Acid Oleic Acid Linoleic Acid Alpha Linolenic Acid
Eicosanoic Acid Heneicosanoic Acid Docosanoic Acid Tricosanoic Acid Tetracosanoic Acid
Pentacosanoic Acid Hexacosanoic Acid Heptacosanoic Acid Octacosanoic Acid Nonacosanoic Acid
Triacontanoic Acid

115

composed of organic acids, largely due to the greater molecular weight of these compounds
(Christoffersen et al., 1998), which leads to lower vapor pressures and increased condensation.
Figure A.11: Cumulative mass fractions of organic acids - engine SOA and α-pinene SOA

A.3.6 Oxidative Potential
The macrophage assay oxidative potential measurement results are presented, on a mass
fraction basis in units of µg-Zymosan/mg-PM in Figure A.12. Engine SOA exhibited greater
oxidative potential as measured by the macrophage assay than α-pinene SOA. The measured
oxidative potential for engine POA was 51.4 (± 64.3) µg-Zymosan/mg-PM, and for engine SOA
it was 1900 (± 255) µg-Zymosan/mg-PM, while for α-pinene SOA the result was 1321 (± 542)
µg-Zymosan/mg-PM. These values are similar in magnitude to the oxidative potential measured
in response to ambient PM2.5 SOA samples collected in Los Angeles and Denver, as reported in
Saffari et al. (2014). The mass fraction results for Los Angeles and Denver PM samples ranged
from 375-1025 and 700-3000 µg-Zymosan/mg-PM, respectively, due to SOA formed primarily
0.00
0.50
1.00
1.50
2.00
2.50
3.00
Engine POA a-Pinene SOA Engine SOA
mass fraction (ng/µg PM)
Phthalic Acid Isophthalic Acid Terephthalic Acid Methylphthalic Acid
Succinic Acid Glutaric Acid Adipic Acid Pimelic Acid
Suberic Acid Azelaic Acid Sebacic Acid Nonadecanoic Acid
Pinonic Acid Tetracosanoic Acid Hexadecanoic Acid Pinonic Acid

116

from vehicle emissions in these urban areas. Traffic emissions have also been shown to be a
significant contributor to the oxidative potential of PM2.5 in several other prior studies in the
metropolitan Los Angeles area (e.g. Daher et al., 2014; Li et al., 2003b; Hu et al., 2008b;
Shirmohammadi et al., 2016; Shirmohammadi et al., 2017) that utilized the dithiothreitol (DTT)
assay as a measure of redox activity.
Figure A.12: Oxidative potential (mass fractions) - engine SOA & POA and α-pinene SOA

The current results are also comparable to those found in a study of the oxidative potential of
PM2.5 resulting from increased biomass burning (i.e. wood smoke) in Thessaloniki during the
winter months (Argyropoulos et al., 2016; Saffari et al., 2013). These authors found the oxidative
potential of ambient PM2.5 samples collected during the winter to be between 700-1200 µg-
Zymosan/mg-PM. In the current study, however, reaction chambers were used to isolate engine
exhaust POA and SOA, so the results may not be directly comparable to those of ambient PM
studies.
0
500
1000
1500
2000
2500
a-Pin SOA Eng SOA Eng POA
Oxidative Potential (µg-Zymosan/mg-PM)

117

Organic acids and WSOC are important components of SOA that generally lead to greater
toxicity. However, while α-pinene SOA contained higher mass-based concentrations of WSOC,
organic acids and PAHs than engine SOA, engine SOA had higher concentrations of hopanes &
steranes, and exhibited greater oxidative potential than α-pinene SOA. These results agree with
Tuet et al. (2017), who also demonstrated a greater oxidative potential in anthropogenic SOA
than biogenic SOA. These authors found that when primary organic aerosol contained
naphthalene (an anthropogenic precursor), the resulting SOA products exhibited the greatest
oxidative potential as indexed by the dithiothreitol (DTT) assay, with the largest effect observed
in a high-NOx environment. The authors attributed the enhanced oxidative potential to nitrogen-
containing aromatic oxidation products resulting from the dominant RO2 + NO reaction in this
condition. The presence of an aromatic ring and/or a nitrite group in SOA products was
postulated to facilitate electron transfer (i.e. oxidation) reactions, thus further potentiating
toxicity of SOA species.
A discussion of aromatic structure, especially that of nitrogenated quinones, contributing to
SOA toxicity is presented in Jiang et al. (2016), who found that the DTT response to 1,4-
naphthoquinone (1,4-NQN), 1,2-naphthoquinone (1,2-NQN), and 9,10-phenanthraquinone
(PQN) produced a much greater DTT response than other SOA components. Verma et al.
(2015b), in a study of ambient PM2.5 collected in and around Atlanta, Georgia, also found that
aromatic quinones, produced as direct products of incomplete combustion (primary aerosols) as
well as oxidization products of primary PAHs (secondary aerosols), exhibited the highest
intrinsic DTT activity. Their results also indicated that the oxidized quinone 5-hydroxy-1,4-
naphthoquinone had a higher oxidative potential than the unoxidized parent compound 1,4-

118

naphthoquinone, demonstrating the important effect of atmospheric aging (photo-oxidation) on
PM toxicity.
In addition to the more comprehensive studies of Rattanavaraha et al. (2011), Jiang et al.
(2016), and Tuet et al., (2017), data from other simpler reaction chamber studies also provide
evidence for the potentiating effect of photo-oxidation on PM oxidative potential. In a study of
naphthalene SOA, McWhinney et al. (2013) found an increased DTT response to 5-hydroxy-1,4-
naphthoquinone as compared to 1,4-naphthoquinone, and Kumagai et al. (2002), in a study of
diesel exhaust particulate (DEP), found that phenanthraquinone, an abundant quinone component
of DEP, catalyzed the formation of oxidative species, as indexed by the DTT assay.
In this study, we demonstrate that the intrinsic oxidative potential of anthropogenic traffic
SOA (i.e. SOA derived from gasoline engine exhaust) is higher than that resulting from biogenic
SOA formation; nonetheless, the results are not starkly disparate and are based on representative
anthropogenic and biogenic sources (i.e. gasoline engine exhaust and α-pinene). Thus, when
determining the overall PM toxicity within a given geographic region, either urban or rural, we
must take into consideration the specific composition of primary sources in the area, both
biogenic and anthropogenic, as well as any temporal variations in in the PM profile, when
determining the specific SOA species formed and thus the overall toxicity of PM in the area. For
example, and as discussed in Jiang et al. (2016), while toluene (a representative species of engine
SOA) may contribute the greatest oxidative potential to PM in urban environments, on a global
scale it is perhaps isoprene in particular, given its much higher worldwide emission rate (i.e. 600
Tg/yr, as reported in Carlton et al. (2009)), that makes the greater contribution to PM toxicity
and thus adverse health effects than either toluene or α-pinene emissions.

119

A.4 Summary and Conclusions
The findings of the current reaction chamber study indicate that gasoline engine exhaust
SOA produces a greater oxidative response than α-pinene SOA, with both secondary aerosols
exhibiting greater redox activity than the primary aerosol precursors contained in engine
emissions. Biogenic (α-pinene) and anthropogenic (engine exhaust) particulate matter, in both
the primary state (POA) and in a secondary state (SOA) resulting from UV-light catalyzed
photo-oxidation reactions, was collected on filters at the outlet of an oxygen flow reactor.
Secondary organic aerosols, composed of oxidized organic compounds, led to greater cellular
oxidative stress and inflammation as compared to POA particulate, as revealed by the alveolar
macrophage assay. This effect was found to be larger in response to engine exhaust SOA than to
α-pinene SOA, thus implicating anthropogenic rather than biogenic PM as the major contributor
to adverse human health effects in urban environments. However, from a global perspective,
region-specific contributions to SOA from both anthropogenic and biogenic sources should also
be considered when attributing toxicity to ambient PM.

Abstract (if available)

Abstract Particulate matter (PM) is perhaps the most ubiquitous form of air pollution affecting urban populations in the world today. With the adverse health outcomes and accompanying deaths due to PM exposures on the rise every year, the need to better understand PM, its toxicity, and possible mitigation strategies has never been more urgent, especially in large urban centers such as Los Angeles, California. Much of the research in this dissertation examines one common measure of PM toxicity, cellular oxidative stress, which has been linked to several health problems, ranging from cardiovascular disease and respiratory distress to neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. Various factors that may reduce or exacerbate this toxicity, including photochemical oxidation and regional geographic and meteorological influences are also examined. Additionally, the long‐term health risks, such as cancer and non‐cancerous organ and tissue damage, posed to Los Angeles commuters facing daily exposures to airborne particulate matter are calculated based on measurements of PM composition and concentration made along the most common commuter routes. ❧ The research findings presented in this dissertation provide further evidence that PM composition and its health effects mediated by oxidative stress are highly complex and susceptible to the influence of several factors, including geographical context, specific source domains, and time of day. While secondary PM that has undergone photochemical oxidation reactions generally has been found to induce a larger proinflammatory response than freshly emitted primary PM, this effect is highly dependent on the dominant species present in PM at any given time and location, and sometimes the reverse may be true. For example, primary motor vehicle emissions, which are dominant in the urban atmosphere near freeways, contain large amounts of redox‐active transition metals such as copper and nickel, as well as water‐insoluble organic compounds such as polycyclic aromatic hydrocarbons (PAHs). Based on the research findings presented herein, these species actually result in greater oxidative stress than secondary PM. While some of these findings may seem counter‐intuitive considering previous research, the use of a more precise sampling methodology, namely the direct aerosol‐into‐liquid collection system, has made it possible to capture PM samples more representative of actual PM exposures urban residents experience. ❧ The research findings presented in this dissertation are an integral component of the ongoing accumulation of knowledge and understanding of urban PM and its health effects. As more data from long‐term epidemiological studies and other sources become available in the future, a more complete picture will undoubtedly continue to develop. This dynamic process of discovery and comprehension is vital for regulatory efforts to continue evolving, becoming ever more refined, efficient, and effective, allowing for cleaner air and the improved health of urban residents around the world.

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Asset Metadata

Creator Lovett, Christopher David (author)

Core Title Toxicity of urban particulate matter: long-term health risks, influences of surrounding geography, and diurnal variation in chemical composition and the cellular oxidative stress response

School Viterbi School of Engineering

Degree Doctor of Philosophy

Degree Program Engineering (Environmental Engineering)

Publication Date 10/08/2018

Defense Date 07/31/2018

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Beirut,commuter health risk,dust episodes,health risk assessment,light rail,Los Angeles,neuroinflammation,OAI-PMH Harvest,on-road emissions,oxidative potential,oxidative stress,photochemistry,PM2.5,primary PM,Sahara and Arabian Deserts,secondary PM,Subway,urban particulate matter (PM)

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Sioutas, Constantinos (committee chair), Ban-Weiss, George (committee member), Finch, Caleb E. (committee member)

Creator Email cd_lovett@yahoo.com,clovett@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-75026

Unique identifier UC11670820

Identifier etd-LovettChri-6788.pdf (filename),usctheses-c89-75026 (legacy record id)

Legacy Identifier etd-LovettChri-6788.pdf

Dmrecord 75026

Document Type Dissertation

Format application/pdf (imt)

Rights Lovett, Christopher David

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA