Research Collection
Doctoral Thesis
Investigating aerosol chemical composition and yields from α-pinene photooxidation derived products: The impact of relativehumidity, NOx/VOC and organic mass concentration
Author(s): Pfaffenberger, Lisa Maria
Publication Date: 2014
Permanent Link: https://doi.org/10.3929/ethz-a-010235287
Rights / License: In Copyright - Non-Commercial Use Permitted
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ETH Library
DISS. ETH NO. 21760
Investigating aerosol chemical composition and yields from α-pinene photooxidation derived products:
The impact of relative humidity, NOx/VOC and organic mass concentration
A thesis submitted to attain the degree of
DOCTOR OF SCIENCES of ETH ZURICH
(Dr. sc. ETH Zürich)
presented by
LISA MARIA PFAFFENBERGER
Dipl.-Meteorologin (Univ.), Ludwig-Maximilians-Universität München
born on 29.01.1985
citizen of Germany
examiners
Prof. Dr. Urs Baltensperger, examiner Prof. Dr. Thomas Peter, co-examiner
Dr. André Prévôt, co-examiner Dr. Harald Saathoff, co-examiner
2014
Contents
Summary ................................................................................................................................. I
Zusammenfassung ................................................................................................................. V
1 Introduction ....................................................................................................................... 1
1.1 Aerosol definition and properties ................................................................................. 2
1.2 Aerosol effects on the Earth’s climate ......................................................................... 4
1.3 Aerosol effects on human health .................................................................................. 7
2 The physical and chemical basis ...................................................................................... 9
2.1 Tropospheric gas-phase chemistry: NOx–VOC catalytic cycles ................................ 10
2.2 Secondary organic aerosol formation and aging ........................................................ 12
2.3 Biogenic organic compounds: focus on α-pinene ...................................................... 15
3 Motivation of the thesis ................................................................................................... 17
4 Methodology ..................................................................................................................... 21
4.1 Smog chamber ............................................................................................................ 22
4.2 Instrumentation .......................................................................................................... 22
4.2.1 Particle phase instruments .................................................................................. 22
4.2.2 Gas-phase instruments ........................................................................................ 23
5 The link between organic aerosol mass loading and degree of oxygenation: an α-
pinene photooxidation study .................................................................................................. 25
Abstract .................................................................................................................................... 26
5.1 Introduction ................................................................................................................ 26
5.2 Method ....................................................................................................................... 29
5.2.1 Experimental setup ............................................................................................. 29
5.2.1.1 Introduction of particle and gas-phase reactants into the chamber ............. 30
5.2.1.2 Instrumental setup ....................................................................................... 33
5.2.2 Estimation of OH exposure ................................................................................. 34
5.2.2.1 OH tracer method ........................................................................................ 34
5.2.2.2 α-Pinene method .......................................................................................... 35
5.2.2.3 Application of the methods to the dataset ................................................... 35
5.2.3 Wall loss correction ............................................................................................ 37
5.3 Results ........................................................................................................................ 37
5.3.1 General reproducibility of the aerosol degree of oxygenation ........................... 37
5.3.2 Dependence of degree of oxygenation on the organic mass concentration ........ 40
5.3.3 Dependence of degree of oxygenation on the OH exposure .............................. 44
5.3.4 Classification of chemical composition using reference mass spectra ............... 45
5.4 Conclusions ................................................................................................................ 47
5.5 Supplementary material ............................................................................................. 49
6 Higher relative humidity and VOC/NOx increase α-pinene secondary organic
aerosol yields ........................................................................................................................... 67
Abstract ................................................................................................................................... 68
6.1 Introduction ................................................................................................................ 69
6.2 Methods ...................................................................................................................... 71
6.2.1 Experimental setup and instrumentation ............................................................ 71
6.2.2 Smog chamber operation and aerosol seeding .................................................... 72
6.2.3 Estimation of the hygroscopic growth factors and liquid water content ............ 75
6.2.4 Determination of OH exposure and extent of α-pinene ozonolysis .................... 76
6.2.5 Determination of suspended and wall-loss-corrected organic mass and yield ... 78
6.3 Results ........................................................................................................................ 81
6.3.1 SOA yield dependence on RH, NOx/α-pinene and aerosol seed composition ... 81
6.3.2 SOA elemental composition ............................................................................... 83
6.3.3 Particle size dependent uptake of organic mass ................................................. 85
6.4 Discussion .................................................................................................................. 90
6.5 Conclusions ................................................................................................................ 92
6.6 Supplementary material ............................................................................................. 94
6.6.1 Transmission and collection efficiency correction ............................................. 94
6.6.2 Seed composition ................................................................................................ 96
7 VIsible light Photosensitized Secondary Organic Aerosol evolution (VIPSOA) ..... 107
7.1 Introduction and scientific objective ........................................................................ 108
7.2 Method ..................................................................................................................... 109
7.3 Results ...................................................................................................................... 111
7.4 Measurement challenges and outlook ...................................................................... 116
8 Final conclusions and outlook ...................................................................................... 119
List of abbreviations and acronyms .................................................................................... 123
Bibliography ....................................................................................................................... 125
Acknowledgements ............................................................................................................. 134
Curriculum vitae ................................................................................................................. 135
I
___________________________________________________________________________
Summary
___________________________________________________________________________
Atmospheric aerosol particles are next to greenhouse gases main contributors to the Earth’s
radiative budget and thus important climate drivers, while their scientific understanding is still
low. An aerosol is a suspension of fine solid or liquid particles in a gas and can be of primary
(e.g. mechanical processes) or secondary (by gas-to-particle conversion) origin. Organic
aerosol (OA) represents a major fraction of the submicron mass loading, whereas sources,
formation processes and chemical transformations of secondary organic aerosol (SOA) are
still poorly known. SOA contributes more than primary organic aerosol (POA) to total OA in
most cities around the world. SOA is mainly formed by oxidation of volatile organic
compounds (VOC), resulting in products with lower saturation vapour pressures and
subsequent condensation on pre-existing particles or nucleation. The volatility and chemical
composition of OA, and in parallel the degree of oxygenation (atomic oxygen to carbon ratio
(O : C)) is changed by gas and particle phase reactions (functionalization, fragmentation and
oligomerisation). Current models have been able to reproduce the SOA loading for a few
urban measurement campaigns by allowing dynamic behaviour (evaporation, oxidation in the
gas phase and re-condensation) of POA and considering highly volatile vapours which remain
preferentially in the gas-phase. Even though the loading could be accurately predicted in those
cases, the models remain still underconstrained in terms of fragmentation, detailed chemical
compositions and volatility of compounds. Measurements of aerosol chemical composition
and loading in the ambient air and in controlled environments as smog chambers (SC) are of
great value to improve model predictions.
The presented work 1) identifies the organic aerosol mass concentration as important factor
responsible for the discrepancy between ambient and SC aerosol degree of oxygenation, 2)
presents the relative humidity and NOx/VOC as important drivers of the aerosol yield from α-
pinene photooxidation and 3) suggests direct irradiation to possibly influence the O : C of
wood burning aerosol. Three sets of systematic experiments were conducted in the stationary
SC of the Paul Scherrer institute (PSI) where the aerosol chemical composition and total mass
concentration was measured by means of Aerodyne high resolution time-of-flight aerosol
mass spectrometers (HR-ToF-AMS) and scanning mobility particle sizers (SMPS).
II
In the first part of the study, the composition of SOA at different organic mass concentrations
from α-pinene photooxidation was compared in terms of the fraction of particulate CO2+, a
surrogate for carboxylic acids, vs. the fraction of C2H3O+, a surrogate for aldehydes, alcohols
and ketones. In addition, the evolution of the atomic hydrogen-to-carbon ratio (H : C) vs. the
O : C was investigated in the Van Krevelen space. Low (near-ambient) organic mass
concentrations were found to be necessary to obtain oxygenation levels similar to those of
low-volatility oxygenated organic aerosol (LV-OOA) commonly identified in ambient
measurements. The effects of organic mass loading and oxidant exposure were decoupled by
inter-experiment comparisons at the same OH exposure (integrated hydroxyl radical (OH)
concentration). An OH exposure between 3 and 25 × 107 cm-3 h was required to increase the
O : C by 0.05 during aerosol aging. For the first time, LV-OOA-like aerosol from the
abundant biogenic precursor α-pinene was produced in a smog chamber by oxidation at
typical atmospheric OH concentrations. A significant correlation between measured SOA and
reference LV-OOA mass spectra is shown for experiments with low OA (< 18 µg m-3).
During the second set of experiments, SOA yields (organic mass formed-to-precursor mass
reacted) from the photooxidation of α-pinene were investigated at low (~25 %) and higher
(~ 60 %) relative humidity (RH), various NOx/VOC ratios (0.04–3.8) and with different seed
chemical compositions. Higher RH increased SOA yields up to six times compared to low
RH, with greater increases for the most hygroscopic/acidic seeds. The yields at NOx/VOC
ratios < 0.1 were 2–11 times higher compared to yields at NOx/VOC ratios of up to 3.8. This
NOx dependence follows the same trend as seen in previous studies for α-pinene SOA. The
chemical signature as observed in Van Krevelen diagrams is dominantly influenced by the
NOx/VOC ratio. While previous studies suggest a major effect of the relative humidity on
particle chemical composition via e. g. oligomerisation, we conclude, based on size-resolved
data, that most of the α-pinene reaction products are not absorbed by the prevailing organic
(nonpolar) and inorganic (polar) seeds, rather, the seed provides the surface for condensation.
In the last section of this study, the possible interaction of visible light irradiation and OA was
investigated. Radiation could turn aerosol compounds into photosensitizers which enhance
reactions by catalysing photochemistry within the particle or at the particle surface. First test
measurements indicated an influence of visible light (λ > 400 nm) on wood burning aerosol,
once SOA was formed and irradiated by UV light. Final conclusions are subject to more
sophisticated measurement techniques.
III
This work elucidates how sensitive SOA composition is to a variety of parameters, even when
mainly focusing on α-pinene as one single precursor. As the O : C influences the chemical,
volatility and hygroscopic properties of ambient aerosol, smog chamber studies must be
performed at near-ambient concentrations to accurately simulate ambient aerosol behaviour.
The SOA yields and chemical composition reported in this thesis is of great value for
improving model parameterizations.
IV
V
___________________________________________________________________________
Zusammenfassung
___________________________________________________________________________
Aerosolpartikel leisten neben Treibhausgasen einen Hauptbeitrag zum Strahlungshaushalt der
Erde und sind folglich wichtige klimawirksame Bestandteile in der Atmosphäre, wohingegen
deren wissenschaftliches Verständnis noch gering ist. Als Aerosol bezeichnet man eine
Suspension aus winzigen festen oder flüssigen Partikeln in einem sie umgebenden Gas, wobei
die Partikel von primärem (z.B. aus mechanischen Prozessen) oder sekundärem (durch Gas-
zu-Partikel Konversion) Ursprung sein können. Organisches Aerosol (OA) repräsentiert einen
Hauptbestandteil der Masse von Partikeln kleiner als einem Mikrometer, allerdings sind
Quellen, Entstehungsprozesse und chemische Umwandlungen von sekundärem organischem
Aerosol (SOA) noch wenig erforscht. SOA trägt in den meisten Städten der Welt mehr zum
organischen Gesamtaerosol bei als primäres organisches Aerosol (POA). Die Bildung von
SOA geschieht vor allem durch die Oxidation von flüchtigen organischen Verbindungen
(VOC), wodurch Produkte mit niedrigeren Sättigungsdampfdrücken entstehen, gefolgt von
anschließender Kondensation auf bereits vorhandenen Partikeln oder Nukleation. Gas- und
Partikelphasenreaktionen (Funktionalisierung, Fragmentierung und Oligomerisation)
verändern die Flüchtigkeit, die chemische Zusammensetzung, und zugleich den
Oxidierungsgrad von OA (atomares Verhältnis zwischen Sauerstoff und Kohlenstoff (O : C)).
Neueste Modelle haben die Aerosolbelastung im Vergleich zu direkten Messungen in einigen
Städten erfolgreich nachsimuliert, indem dynamisches Verhalten (Verdampfung, Oxidierung
in der Gasphase und nochmalige Kondensation) von POA zugelassen wurde und indem
Produkte berücksichtigt wurden, die extrem flüchtig sind und bevorzugt in der Gasphase
verweilen. Obwohl in diesem Fall die Aerosolbelastung korrekt vorhergesagt werden konnte,
sind Modelle nichtdestotrotz in Bezug auf die Fragmentierung, die detaillierte chemische
Zusammensetzung und die Flüchtigkeit der Substanzen nicht vollständig beschrieben.
Messungen der chemischen Zusammensetzung von Aerosolen und der Partikelbelastung in
Außenluft und in kontrollierten Räumen wie z. B. Smogkammern (SC) sind daher von großer
Bedeutung, um Modellvorhersagen zu verbessern.
Die hier vorliegende Arbeit 1) identifiziert die organische Massenkonzentration als einen
wichtigen Faktor für die Diskrepanz zwischen dem Oxidierungsgrad von atmosphärischem
VI
und von in SC generiertem Aerosol; 2) verdeutlicht die Wichtigkeit der relativen Feuchte und
des NOx/VOC Verhältnisses für die Aerosol-Ausbeute aus der Photooxidation von α-Pinen
und 3) deutet darauf hin, dass sichtbares Licht vermutlich das O : C von
Holzverbrennungsaerosol beeinflusst. In der stationären SC des Paul Scherrer Instituts (PSI)
wurden drei systematische Versuchsreihen durchgeführt, während derer die chemische
Zusammensetzung des Aerosols mittels eines hochauflösendem Aerodyne Flugzeit
Massenspektrometers (HR-ToF-AMS) und die Gesamtmassenkonzentration mittels eines auf
der Mobilität der Partikel basierenden Größenmessgeräts (SMPS) gemessen wurden. Im
ersten Teil der Studie wurde die Zusammensetzung von SOA, durch Photooxidation von α-
Pinen entstanden, bei verschiedenen Massenkonzentrationen in Bezug auf dessen Anteil an
CO2+ in der Partikelphase (einem Proxy für Karbonsäuren) gegenüber dem Anteil an C2H3O
+
(einem Proxy für Aldehyde, Alkohole und Ketone) verglichen. Zusätzlich wurde die
Veränderung des atomaren Wasserstoff-Kohlenstoff-Verhältnisses (H : C) gegenüber O : C
im Van Krevelen Diagramm untersucht. Es wurde herausgefunden, dass niedrige
(vergleichbar mit der realen Atmosphäre) organische Massenkonzentrationen nötig sind, um
Oxidierungsgrade zu erreichen, welche vergleichbar sind mit jenen von schwerflüchtigem
oxidiertem organischem Aerosol (LV-OOA), das üblicherweise in atmosphärischen
Messungen identifiziert wird. Die Effekte der organischen Massenkonzentration und der
„OH-Exposition“ (integrierte Hydroxyl-Radikal (OH) Konzentration) wurden entkoppelt,
indem Experimente bei gleicher OH-Exposition verglichen wurden. Eine OH-Exposition
zwischen 3 und 25 × 107 cm-3 h war erforderlich, um das O : C während der Aerosolalterung
um 0.05 zu erhöhen. Zum ersten Mal wurde in einer Smogkammer LV-OOA-ähnliches
Aerosol aus dem oft vorhandenen biogenen Vorläufergas α-Pinen durch Oxidation bei typisch
atmosphärischen OH-Konzentrationen produziert. Massenspektren von gemessenem SOA
zeigen eine signifikante Korrelation mit LV-OOA-Referenzspektren bei Experimenten mit
niedrigem OA (< 18 µg m-3).
Während der zweiten Experimentreihe wurden SOA-Ausbeuten (d.h. gebildete organische
Masse/ reagierte Masse eines Vorläufergases) während der Photooxidation von α-Pinen bei
niedriger (~ 25 %) und hoher (~ 60 %) relativer Feuchte (RH), verschiedenen NOx/VOC
Verhältnissen (0.04–3.8) und unterschiedlichen chemischen Zusammensetzungen eines
vorgelegten Aerosols („Seed-Aerosol“) untersucht. Eine höhere Feuchte erhöhte die SOA-
Ausbeute hierbei um bis zu sechs Mal im Vergleich zu einer niedrigen Feuchte, wobei höhere
Zunahmen mit denjenigen „Seed-Aerosolen“ erreicht wurden, die am hygroskopischsten und
sauersten waren. Die Ausbeuten bei einem NOx/VOC-Verhältnis < 0.1 waren 2–11-mal höher
VII
als diejenigen bei einem NOx/VOC-Verhältnis von bis zu 3.8. Die NOx-Abhängigkeit folgte
dem gleichen Trend, der in früheren Studien zu α-Pinen-SOA gefunden wurde. Die chemische
Signatur, die in Van Krevelen-Diagrammen untersucht wurde, wird in erster Linie durch das
NOx/VOC-Verhältnis beeinflusst. Frühere Studien schlugen einen großen Einfluss der
relativen Feuchte auf die chemische Zusammensetzung der Partikel vor, z. B. einhergehend
mit Oligomerisation. Dahingegen folgern wir, basierend auf größenaufgelösten Daten, dass
die meisten α-Pinen Reaktionsprodukte nicht von vorhandenen organischen (unpolar) und
anorganischen (polar) „Seed-Aerosolen“ absorbiert werden, sondern das „Seed-Aerosol“
vielmehr eine Oberfläche für Kondensation bietet.
Im letzten Teil der Studie wurde eine mögliche Wechselwirkung von direkter Licht-
Einstrahlung und OA untersucht. Licht könnte Bestandteile des Aerosols in Photosensitizer
umwandeln, welche durch Reaktionen innerhalb eines Partikels oder auf der
Partikeloberfläche photochemische Prozesse katalysieren. Erste Testexperimente zeigten
einen Einfluss von sichtbarem Licht (λ > 400 nm) auf Holzverbrennungsaerosol,
vorausgesetzt, SOA wurde vorher gebildet und mit UV-Licht bestrahlt. Für endgültige
Schlussfolgerungen sind jedoch noch ausgereiftere Messtechniken notwendig.
Diese Arbeit macht deutlich, wie stark die SOA-Zusammensetzung von einer Fülle an
Parametern abhängt, auch wenn wir uns mit α-Pinen auf ein einziges Vorläufergas
konzentriert haben. Um die Eigenschaften von atmosphärischem Aerosol wahrheitsgetreu zu
simulieren, müssen Smogkammerstudien bei Konzentrationen, die jenen in der Atmosphäre
ähnlich sind, durchgeführt werden. Dadurch werden die chemischen Eigenschaften wie das
O : C-Verhältnis, sowie die Flüchtigkeit und die Hygroskopizität des atmosphärischen
Aerosols beeinflusst. Die Ausbeuten und chemischen Zusammensetzungen von SOA, die in
dieser Dissertation präsentiert werden, sind von großer Wichtigkeit, um Parametrisierungen in
Modellen zu verbessern.
___________________________________________________________________________
1 Introduction
___________________________________________________________________________
2 1 Introduction
1.1 Aerosol definition and properties
Particles in the atmosphere originate from natural sources, such as windborne dust, sea spray
and volcanoes, and from anthropogenic activities, such as industrial processes or combustion
of fuels. Whereas an aerosol is technically defined as a suspension of fine solid or liquid
particles in a gas, common usage refers to the aerosol as the particulate component only.
Emitted directly as particles (primary aerosol) or formed in the atmosphere by gas-to-particle
conversion processes (secondary aerosol), atmospheric aerosols are generally considered to be
the particles that range in size from a few nanometers (nm) to tens of micrometers (µm) in
diameter. The term PMx, defined as particulate matter with an aerodynamic diameter smaller
than x µm, is often used to describe the aerosol mass concentration (e.g. PM1, PM2.5). Once
airborne, particles can change their size and composition by condensation of vapours or by
evaporation, by coagulating with other particles, by chemical reaction, or by activation in the
presence of water supersaturation to become fog or cloud droplets (Seinfeld and Pandis,
2006). There are several properties of particles that are important for their role in atmospheric
processes. These include their number concentration, their mass, size, chemical composition,
and aerodynamic and optical properties. Of all these properties, particle size is the most
important. It is not only related to the source or processing of the particles, but also to their
effects on health, visibility, and climate (Finlayson-Pitts and Pitts, 2000).
Atmospheric removal processes can be divided into two groups: dry deposition and wet
deposition. Dry deposition refers to the direct transfer of species to the earth’s surface without
the aid of precipitation. Wet deposition encompasses all processes by which species are
transferred to the earth’s surface in aqueous form like rain, snow or fog. Whereas atmospheric
trace gases have lifetimes ranging from less than a second to a century or more, residence
times of particles in the troposphere vary only from a few days to a few weeks, depending on
their shape, density and chemical composition, as well as precipitation frequency (Seinfeld
and Pandis, 2006). Figure 1.1 displays formation, growth, chemical transformation and
removal processes of atmospheric aerosols and gases as a function of particle diameter (Raes
et al., 2000).
Aerosols interact with radiation by absorption and scattering, the sum of which, the overall
attenuation, is defined as extinction. In addition to the size, the radiative effects of a
population of particles depend on their composition through compound and mixture specific
refractive indices. There are substances mainly absorbing (e.g. black carbon (BC)) substances
1.1 Aerosol definition and properties 3
Figure 1.1. Scheme of microphysical processes influencing the size distribution and chemical composition of atmospheric aerosol. The scheme highlights the large range of sizes that are involved in the formation and evolution of aerosol particles, and how aerosols participate in atmospheric chemical processes through homogeneous, heterogeneous and in-cloud reactions (Raes et al., 2000).
exclusively scattering (e.g. sulfate). The atmospheric aerosol is generally a mixture of species
from a number of sources. The aerosol mixing state depends on how all the components are
distributed among the particles (Seinfeld and Pandis, 2006). Figure 1.2 shows a schematic of
possible mixtures: fresh or aged externally mixed aerosol and fresh or aged internally mixed
aerosol.
Figure 1.2. Schematic of externally and internally mixed aerosol. Particles vary in size, chemical compositions and the fractions of species within one particle.
4 1 Introduction
In nature, a fresh externally mixed aerosol population could represent black and organic
carbon emissions mixed with sea salt background aerosol, the aged aerosol could be covered
with a layer of secondary organic aerosol. The internally mixed aerosol population could arise
from new particle formation in a clean background atmosphere, from coating of BC with
SOA or ammonium sulfate, or from droplet coalescence within clouds (Andreae et al., 1986).
An ideal internally mixed aerosol can be produced in laboratories.
When a light-absorbing compound is present, all particles in an internal mixture exhibit some
absorption, whereas in an external mixture, only part of the aerosol exhibits absorption. The
ability of the aerosol to absorb water, defined as the hygroscopicity, is also influenced by the
mixing state of the aerosol. Assuming that both hygroscopic and non-hygroscopic
components are present, in an internal mixture every particle (of a given size) exhibits
proportionally the same growth as RH is increased; in an external mixture, only the
hygroscopic particles grow (Seinfeld and Pandis, 2006).
1.2 Aerosol effects on the Earth’s climate
Aerosols can influence the Earth’s climate in two ways: by aerosol-radiation interactions (ari)
and aerosol-cloud interactions (aci). In the IPCC report (Intergovernmental Panel on Climate
Change, IPCC, 2013b) large efforts have been made to determine the effects of both types of
interactions on the Earth’s radiative budget. The commonly used parameter to quantify the
contribution of various drivers to climate change is the radiative forcing (RF), defined as the
net change in the energy balance of the Earth system due to some imposed perturbation, in
W m-2 and averaged over a particular period of time. Recent research has clarified the
importance of distinguishing forcing and rapid adjustments from feedbacks: Forcings
associated with agents such as greenhouse gases and aerosols act on the global mean surface
temperature through the instantaneous change in the global radiative (energy) budget. Rapid
adjustments arise when forcing agents, by altering flows of energy internal to the system,
affect cloud cover or other components of the climate system and thereby alter the global
radiative budget indirectly. In contrast, feedbacks are associated with changes in climate
variables that are mediated by a change in global-mean surface temperature. Furthermore one
can distinguish between the traditional concept of radiative forcing (RF), defined as the
change in the radiative budget over a given time period, and the relatively new concept of
effective radiative forcing (ERF) which includes in addition rapid adjustments (IPCC, 2013b).
1.2 Aerosol effects on the Earth’s climate 5
Figure 1.3 links the former terminology of aerosol direct, semi-direct and indirect effects with
the terminology used in the recent IPCC report (IPCC, 2013b). The radiative forcing from
aerosol-radiation interactions (RFari) encompasses radiative effects from anthropogenic
aerosols before any adjustment takes place, and corresponds to what is usually referred to as
the aerosol direct effect. Rapid adjustments induced by aerosol radiative effects on the surface
energy budget, the atmospheric profile and cloudiness contribute to the effective radiative
forcing from aerosol-radiation interactions (ERFari). They include what has earlier been
referred to as the semi-direct effect. The radiative forcing from aerosol-cloud interactions
(RFaci) refers to the instantaneous effect on cloud albedo due to changing concentrations of
cloud condensation and ice nuclei, also known as the Twomey effect. All subsequent changes
to the cloud lifetime and thermodynamics are rapid adjustments, which contribute to the
effective radiative forcing from aerosol-cloud interactions (ERFaci) (IPCC, 2013b).
Figure 1.3. Schematic of the new terminology used in Assessment Report AR5 for aerosol-radiation and aerosol- cloud interactions and how they relate to the terminology used in the earlier AR4 report (Forster et al., 2007). The blue arrows depict solar radiation, the grey arrows terrestrial radiation, and the brown arrow symbolises the importance of couplings between the surface and the cloud layer for rapid adjustments (IPCC, 2013b).
6 1 Introduction
Figure 1.4 shows the RF over the industrial era (2011 relative to 1750) by emitted
compounds, putting the aerosol climate effects into relation with the RFs of greenhouse gases,
surface albedo (defined as ratio of reflected to incident radiation) changes due to land use and
natural changes in solar irradiance (IPCC, 2013a). For all gases, the changes in emissions and
changes in abundance are considered. All changes leading to an increase of greenhouse gas
(CO2, H2O, CH4, N2O, O3 and halocarbons) concentrations have a positive effect on the RF.
CO2 represents the dominant positive RF by both, abundance and emitted compound. NOx
caused a positive RF by increased O3 production and a negative RF by influencing the
lifetime of CH4 and reducing its abundance (for a detailed description of the tropospheric gas-
phase chemistry, see Sect. 2.1) and through contributions to nitrate aerosol formation.
Figure 1.4. Radiative forcing estimates in 2011 relative to 1750 and aggregated uncertainties for the main drivers of climate change. Values are global average radiative forcing partitioned according to the emitted compounds or processes that result in a combination of drivers. Best estimates of the net radiative forcing are shown as black diamonds with corresponding uncertainty intervals (numerical values and confidence level in the net forcing on the right: VH – very high, H – high, M – medium, L – low, VL – very low). Total anthropogenic radiative forcing is provided for three different years relative to 1750 (IPCC, 2013a).
1.3 Aerosol effects on human health 7
Emissions of BC have a positive RF through aerosol-radiation interactions and BC on snow
and ice. Scattering aerosol comprising mineral dust, sulfate, nitrate and organic carbon show
negative RF (IPCC, 2013b).
The total effective radiative forcing due to aerosols, assessed to be –0.9 (–1.9 to –0.1) W m–2
with medium confidence [ERFari = –0.45 (–0.95 to +0.05) W m–2, ERFaci = –0.45 (–1.2 to
0.0) W m–2, excluding the effect of absorbing aerosol on snow and ice], is counteracting the
ERF of well-mixed greenhouse gases (CO2, CH4, N2O and halocarbons), assessed to be +2.83
(+2.26 to +3.40) W m–2 with very high confidence (IPCC, 2013b). Due to the high uncertainty
of the aerosol ERF, research on the global and regional aerosol budget and composition is
needed to better evaluate the present and future impact of aerosols on the climate.
1.3 Aerosol effects on human health
Particles can affect human health by inhalation and followed inflammation of the lung or
cardiopulmonary diseases. Three main particle deposition mechanisms in the respiratory tract
include inertial impaction, gravitational settling and diffusion. Particles larger than 5 µm in
diameter are deposited in the upper respiratory tract where also particles smaller than a few
tens of nm are efficiently removed by diffusion (Maynard and Kuempel, 2005). Particle
deposition modelling indicates that up to 90 % or more of the inhaled mass fraction of
particles smaller than 100 nm deposits in the respiratory tract, with up to approximately 50 %
in the alveolar region, the deepest part of the lung (ICRP, 1994). Ultrafine particles below
100 nm diameter are potentially the most dangerous, because they own the largest surface
area and highest content of potentially toxic hydrocarbons among all particular matter
sources. Finally they can penetrate deeper into the lung tissue than fine or coarse particles
(Oberdörster and Utell, 2002; Nel, 2005). A correlation between increased mortality and
PM2.5 levels as well as a decrease in mortality for decreased PM2.5 levels was found for six
cities in the US (Dockery et al., 1993; Laden et al., 2006; Lepeule et al., 2012). Pope III et al.
(2009) found that each 10 µg m-3 increase in PM2.5 concentration was associated with
approximately a 4 %, 6 % and 8 % increased risk of all-cause, cardiopulmonary, and lung
cancer mortality, respectively.
___________________________________________________________________________
2 The physical and chemical basis
___________________________________________________________________________
10 2 The physical and chemical basis
2.1 Tropospheric gas-phase chemistry: NOx–VOC catalytic cycles
Volatile organic compounds (VOCs) are precursors for secondary organic aerosol (SOA)
formation via the condensation of low volatility and semi-volatile oxidation products. Their
gas-phase reaction pathways are highly dependent on the ratio between nitrogen oxide (NOx)
and VOC concentration as shown in Figure 2.1. Tropospheric O3 concentrations are
dependent on the reaction chain lengths of NOx ([NOx] = [NO] + [NO2]) and HOx ([HOx] =
[OH] + [HO2] + [RO2]) catalytic cycles (Thornton et al., 2002). An important measure of
atmospheric ozone-forming oxidation cycles is the ozone production efficiency (OPE). NOx
can be viewed as the catalyst in O3 formation, because it gets cycled back and forth between
NO and NO2 in O3 generation. The OPE can be described by the formation of NO2 leading to
ozone production ( ) versus the loss of NOx ( ) which is mostly due to reaction of NO2
with OH, here as an example for HO2 (Seinfeld and Pandis, 2006):
OPE
(2.1)
where and are the reaction rates of HO2 with NO and OH with NO2,
respectively. Hydroxyl radicals (OH ̇ ) are mainly produced by the photolysis of ozone (next
to HONO, H2O2 and aldehyde photolysis):
O H O → 2OH ̇ O (R 2.1)
OH ̇ radicals react with VOCs to produce alkyl radicals which in turn react with oxygen to
give alkyl-peroxy radicals:
RCH OH∙ → RCH ∙ H O (R 2.2)
RCH ∙ O M → RCH O ∙ M (R 2.3)
RCH O ∙ NO → RCH O∙ NO (R 2.4)
NO →NO O (R 2.5)
O O → O (R 2.6)
In addition to O3 production and re-cycling of NOx, this reaction chain leads to reduction of
VOCs which are then able to turn into low-volatile products undergoing gas-to-particle
conversion. Three reaction regimes have been defined involving the OPE: NOx limited, VOC
limited and transition regime:
2.1 Tropospheric gas-phase chemistry: NOx–VOC catalytic cycles 11
NOx limited or low NOx regime: HO2˙ (hydroperoxyl radicals) react at low NOx
concentrations, instead of with NO, with alkyl-peroxy radicals (R 2.7) or do self-reaction to
form hydrogen peroxide (R 2.8). For a fixed HOx source at low NOx concentrations, O3
increases linearly with increases in NOx concentrations.
RCH O ∙ HO ∙ → RCH OOH O (R 2.7)
HO ∙ HO ∙ H O → H O O H O (R 2.8)
VOC limited or high NOx regime: At higher NOx concentrations, effective ozone production
rates decrease with increasing NOx due to the enhanced nitric acid (HNO3) formation, which
in turn reduces NOx concentration and consumes OH instead of reacting with RCH3 (R 2.2):
NO OH∙ → HNO (R 2.9)
Figure 2.1. Reaction scheme of coupled NOx and VOC cycle producing oxidized species and O3 that can be terminated by the formation of HNO3 (mainly high NOx regime) or the formation of peroxides (mainly low NOx regime) (Guderian, 2000).
Transition regime: Between the NOx limited and VOC limited regimes, the NOx/VOC ratio
is at its optimum to efficiently produce and recycle OH radicals and therefore maximize O3
production and degradation of VOCs (Seinfeld and Pandis, 2006; Thornton et al., 2002).
EKMA-diagrams (Empirical Kinetic Modeling Approach, EPA, 1977) show highest for
VOC (ppmC)/NOx(ppm) of approximately 8/1, a typical ratio in the transition regime. The
VOC-limited, transition and NOx limited regime can be observed when following an air
12 2 The physical and chemical basis
parcel from a city with high NOx emissions on its way to rural areas with less pollution and
more dominant VOC emissions compared to NOx or in SC experiments when starting with
high NOx.
2.2 Secondary organic aerosol formation and aging
The dynamic nature of the semi-volatile species resulting from the NOx-VOC cycling is
important for their absolute yields, defined as the ratio of aerosol mass formed to gas-phase
precursor mass reacted. Depending on their saturation vapor pressure and inferred volatility, a
higher or lower percentage of the total concentration of a compound is found in the particle
phase. Gas-phase oxidation reactions can reduce volatility by the addition of polar functional
groups or increase it by the cleavage of carbon–carbon bonds (Kroll and Seinfeld, 2008). As a
consequence, SOA yields and degree of oxygenation (described by the O : C ratio) may not
be constant for one precursor compound, but subject to the extent to which it was exposed to
oxidants.
Barley et al. (2009) comprehensively summarized the history of partitioning formulations:
The partitioning of semi-volatile organic components was originally thought to be dominated
by adsorption (Pankow, 1987), before Pankow et al. (1994) developed an equilibrium
partitioning model to distinguish between absorptive partitioning into a condensed phase and
adsorption onto the particle surface. Odum et al. (1996) described the partitioning by splitting
semi-volatile products into two volatility bins. Pankow et al. (2001) developed the absorptive
partitioning model to describe the gas/particle partitioning of each component in a complex
multicomponent system. The condensation of multiple organic compounds into an aerosol
needs to take account of interactions between molecules in the condensed phase (deviations
from Raoult’s Law) as well as the volatility of the components. The absorptive partitioning
model provides a mathematically simple method of predicting the condensed phase
composition in a multicomponent system at temperatures and pressures relevant to the
atmosphere. Donahue et al. (2006) further developed the model to consider a number of
condensable compounds with a broad range of volatility (volatility basis set (VBS)). This
approach allows use of large numbers of potentially condensable compounds by binning them
according to their saturation concentration ( ∗) value. The amount of condensed material is
calculated by summing all components i ensuring mass balance between the two phases for
each component considered.
2.2 Secondary organic aerosol formation and aging 13
Defining a partitioning coefficient ξi for compound i given its ∗ value:
,
,
,
, ,1 ,
,1
, ∙1
∗
(2.2)
With: ,,
, ∙ ,
∗ (2.3)
where caer,i and cg,i are the mass concentrations of compound i in the condensed and gas phase,
respectively, and ctot,i the sum of both, all in µg m-3. Kp,i is the partitioning constant of
compound i. coa is the total particle-phase concentration of compounds miscible with
compound i. R is the ideal gas constant, T (K) the temperature, Mi (g mol-1) molecular weight
of species i, ζ is a molality-based activity coefficient for compound i in the liquid phase and
, is the saturation vapour pressure of pure compound i at temperature T. Following Eq.
(2.3), the partitioning constant Kp,i can be increased by decreasing the molality-based activity
coefficient, the vapour pressure or the temperature.
The total mass of condensed miscible organic material, coa, is given by the sum of the
products of the individual total component concentrations in both phases and their partitioning
coefficients: ∑ ∙ . When ∗ is equal to coa, half of the semi-volatile mass resides
in the particle phase and the other half in the gas phase. Figure 2.2 (Kroll and Seinfeld, 2008)
shows the fractions ξ of semi-volatile compounds i in the particle phase using a 2-product
approach (Odum et al., 1996; Figure 2.2a–b) and a broader volatility distribution (Donahue et
al., 2006; Figure 2.2c–d). Partitioning plots at two organic mass loadings coa = 1 µg m-3
representative for remote areas (left panels) and coa = 10 µg m-3 representative for urban areas
(right panels), show the increased particulate fraction for semi-volatile compounds for
increased coa. Note that these plots show only the fraction ξ of each semi-volatile compound
in the particle phase; particle-phase concentrations are obtained by multiplying ξ by total mass
concentration of each semi-volatile compound. The figure visualizes the difficulty to
represent the whole volatility range with only two surrogate compounds.
14 2 The physical and chemical basis
The aerosol yield from a precursor gas-phase concentration is defined as the ratio between
organic aerosol mass formed (Δcoa) per mass of hydrocarbon reacted (ΔHC) (Kroll and
Seinfeld, 2008):
∆∆
∙ ∑ ,
, (2.4)
where αi is the mass yield of compound i. The SOA yield from a given precursor is therefore
not a stoichiometric quantity, but rather increases with increasing total organic particulate
loading.
Figure 2.2. Representation of gas–particle partitioning for a complex mixture of semi-volatiles using (a–b) the ‘two-product model’, and (c–d) the ‘volatility basis set’. Partitioning at two mass loadings of organic aerosol (1 and 10 mg m-3) is shown for each. (Kroll and Seinfeld, 2008, adapted).
Kroll and Seinfeld (2008) focused on three primary factors determining volatility of organic
compounds in the atmosphere: (1) oxidation reactions of gas-phase organic species, which
lower volatility by addition of functional groups but can also increase volatility by cleavage of
carbon-carbon bonds; (2) reactions in the particle (condensed) phase, which can change
volatility either by oxidation or formation of high-molecular-weight species; and (3) the
extent to which these reactions occur, as the volatility distribution of oxidation products will
2.3 Biogenic organic compounds: focus on α-pinene 15
continuously evolve as a result of ongoing chemistry. Those processes are illustrated in Figure
2.3 from Jimenez et al. (2009).
Figure 2.3. Fragmentation, functionalization or oligomerisation change volatility (and the degree of oxygenation). The branching ratio (β) determines if functionalization will reduce volatility, whereas fragmentation can generate more-volatile species, which are less likely to partition to the OA (Jimenez et al., 2009, adapted).
2.3 Biogenic organic compounds: focus on α-pinene
Biogenic volatile organic compounds (BVOC) are emitted mainly from vegetation and are
therefore underlying seasonal variations, where highest BVOC emissions occur at high
temperatures and high solar radiation. The annual global VOC flux was estimated to be 1150
Tg C, composed of 44 % isoprene, 11 % monoterpenes (such as α-/β-pinene), 22.5 % other
reactive VOC, and 22.5 % other VOC (Guenther et al., 1995). Globally, BVOC emissions, are
one order of magnitude more abundant than anthropogenic VOCs (Guenther et al., 2006).
Steinbrecher et al. (2009) presented detailed BVOC emission indices for a large range of tree
species. α-Pinene (29 %) and β-pinene (21 %) represent the highest emitted fractions of
monoterpenes (C10H16), which consist in general of two isoprene units (C5H8). The model
compound mainly used in this thesis was α-pinene (M = 136.2340 g mol-1 (NIST)) with its
structure shown next to isoprene in Figure 2.4.
16 2 The physical and chemical basis
Figure 2.4. Chemical structure of a) the monoterpene α-pinene (C10H16) and b) isoprene (C5H8).
BVOC play a key role in aerosol formation and yearly fluxes of 12–70 Tg yr-1 biogenic SOA
(BSOA) were estimated by “bottom-up” models (Hallquist et al., 2009). “Bottom-up”
methods combine known or inferred biogenic (most notably isoprene and terpenes) and/or
anthropogenic VOC precursor fluxes in global models with laboratory data from SOA
formation experiments to obtain a global organic aerosol field.
The global emission of monoterpenes is 4 times lower than that of isoprene, but its influence
on the aerosol burden is higher due to the high SOA formation potential. α-Pinene SOA yields
up to 20 % at ~50 µg m-3 organic mass concentration (Hao et al., 2011, and references
therein), while even 28.5 % for 281 µg m-3 OA (Cocker et al., 2001) were reported, whereas
isoprene yields span much lower values: < 1 % (Kleindienst et al., 2006), 1–3 % for 10–
100 µg m-3 OA (Dommen et al., 2009).
Radiocarbon dating (14C) methods indicate that in summer non-fossil, biogenic sources are
dominant in Zürich with 60 % of OC, where SOA prevails (Szidat et al., 2006). Also the high
non-fossil SOA fraction together with a high contribution of monoterpenes to SOA in
Marseille in summer time indicated that biogenic VOC are important SOA precursors (El
Haddad et al., 2013). In winter, a high fraction of non-fossil SOA can originate from wood
burning emissions, and the contribution of biogenic sources is more difficult to be quantified.
___________________________________________________________________________
3 Motivation of the thesis
___________________________________________________________________________
18 3 Motivation of the thesis
Organic aerosol represents a major fraction of the submicron mass loading, whereas sources
of SOA are still poorly known. Aerosol has a large effect on the Earth’s climate, attributed
with a large uncertainty as discussed in Section 1.2. Comparing modelled and observed SOA
(Figure 3.1) during measurement campaigns in different cities all over the world, showed that
the VBS approach (Sect. 2.2) represents measured SOA much better than the traditional
approach where POA is assumed non-volatile and SOA less dynamic (Hodzic et al., 2010).
Still, many processes influencing the chemical composition and amount of SOA are unknown.
Figure 3.1. Comparison of observed to predicted SOA ratios. Blue symbols represent estimates of the traditional SOA approach, while red refers to the volatility basis set. (Hodzic et al., 2010 and references therein)
This thesis is contributing to a better understanding of SOA by investigating chemical
composition and yields from the photooxidation of the atmospheric abundant aerosol
precursor α-pinene, when being exposed to various atmospherically relevant experimental
conditions. We studied BVOC because it is evident from the NOx-VOC catalytic cycle
(described in Sect. 2.1) that with reducing anthropogenic emissions of both VOC and NOx,
biogenic sources become increasingly important in atmospheric chemical processes
(Steinbrecher et al., 2009).
The aim of this study is to examine the impact of the mass concentration on SOA chemical
composition as well as the NOx/VOC ratios and particulate water content, contributing to the
total absorptive mass, on SOA chemical composition and yields. This is performed by varying
α-pinene initial concentrations, NOx/α-pinene ratios, aerosol seed composition
(hygroscopicity, acidity) and relative humidity. The relationship between O : C and organic
mass concentration as well as SOA yields reported here may aid the parameterization of the
3 Motivation of the thesis 19
α-pinene SOA dependence on total organic mass concentration, NOx and particulate water for
use in atmospheric models.
___________________________________________________________________________
4 Methodology
___________________________________________________________________________
22 4 Methodology
4.1 Smog chamber
Smog chambers provide a controlled isolated environment to investigate the formation and
aging of aerosols (Alfarra et al., 2006; Paulsen et al., 2005; Kalberer et al., 2004). The PSI
smog chamber is a 27-m3 bag made of a fluorocarbon film, enclosed in a temperature-
controlled housing. A schematic of the chamber is shown in Figure 4.1. The chamber can be
irradiated with four xenon arc lamps (16 kW total) to simulate the solar spectrum with the
intensity of a Swiss winter day at noon and with 80 recently installed black lights (Philips,
Cleo performance 100W/R) to accelerate oxidation by increased UV radiation, with emission
between 300–400 nm wavelength (light characterization in Platt et al. (2013).
Figure 4.1. Plan view of the reaction chamber and enclosure (Paulsen et al., 2005).
4.2 Instrumentation
The temperature (T) and RH measurement was optimized by passing sampling air through a
radiation shielded sensor.
4.2.1 Particle phase instruments
The Aerodyne high resolution time of flight aerosol mass spectrometer (HR-ToF-AMS,
Aerodyne Research, Inc., Billerica, MA, USA) provides online measurements of real-time
non-refractory chemical speciation (organics, ammonium, nitrate, sulfate, chloride) and mass
4.2 Instrumentation 23
loading as a function of particle size on the principle of thermal vaporization and electron
impact (DeCarlo et al., 2006). The HR-TOF-AMS contains a time-of-flight mass spectrometer
which allows distinguishing of different elemental compositions (ions) at the same unit mass
with a good resolution power for m/z <120. The high pressure lens PM2.5, increasing the upper
particle size cut off from ~ 1000 nm (standard lens) till ~ 2500 nm (Williams et al., 2013) is
an important improvement.
The scanning mobility particle sizer (SMPS) measures the size distribution of fine particles by
separation based on their electrical mobility. The sampled air is usually dried prior to entering
the particle-phase instruments, to minimize loss of large particles and the influence of water
on the HR-ToF-AMS measurement.
4.2.2 Gas-phase instruments
The proton transfer reaction mass spectrometer (PTR-MS) measures with unit mass resolution
molecules which have a proton affinity higher than that of water (165.2 kcal mol-1). The main
constituents of the air (nitrogen, oxygen, argon, carbon dioxide) have a lower proton affinity
than water and the measurement of volatile organic compounds of low concentration is
therefore facilitated (Lindinger et al., 1998; Hellén et al., 2008).
A chemiluminescence-based NOx instrument (Monitor Labs 9841A NOx analyzer) and a
modified NOx instrument including a photolytic NO2-to-NO converter (Thermo
Environmental Instruments 42C trace level NOx analyzer equipped with a blue light
converter) and two ozone monitors (Monitor Labs 8810 ozone analyzer, Environics S300
ozone analyzer) monitor the gas phase in the chamber.
___________________________________________________________________________
5 The link between organic aerosol mass
loading and degree of oxygenation:
an α-pinene photooxidation study
___________________________________________________________________________
L. Pfaffenberger1, P. Barmet1, J. G. Slowik1, A. P. Praplan1,+, J. Dommen1, A. S. H.
Prévôt1 and U. Baltensperger1
1Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen, Switzerland
+Now at: Department of Physics, University of Helsinki, Helsinki, Finland
Published in Atmospheric Chemistry and Physics, 13, 6493-6506, doi:10.5194/acp-13-6493-2013
26 5 The link between organic aerosol mass loading and degree of oxygenation
Abstract
A series of smog chamber (SC) experiments was conducted to identify factors responsible for
the discrepancy between ambient and SC aerosol degree of oxygenation. An Aerodyne high-
resolution time-of-flight aerosol mass spectrometer is used to compare mass spectra from α-
pinene photooxidation with ambient aerosol. Composition is compared in terms of the
fraction of particulate CO2+, a surrogate for carboxylic acids, vs. the fraction of C2H3O
+, a
surrogate for aldehydes, alcohols and ketones, as well as in the Van Krevelen space, where
the evolution of the atomic hydrogen-to-carbon ratio (H : C) vs. the atomic oxygen-to-carbon
ratio (O : C) is investigated. Low (near-ambient) organic mass concentrations were found to
be necessary to obtain oxygenation levels similar to those of low-volatility oxygenated
organic aerosol (LV-OOA) commonly identified in ambient measurements. The effects of
organic mass loading and OH (hydroxyl radical) exposure were decoupled by inter-
experiment comparisons at the same integrated OH concentration. An OH exposure between3
and 25 × 107 cm-3 h is needed to increase O : C by 0.05 during aerosol aging. For the first
time, LV-OOA-like aerosol from the abundant biogenic precursor α-pinene was produced in a
smog chamber by oxidation at typical atmospheric OH concentrations. Significant correlation
between measured secondary organic aerosol (SOA) and reference LV-OOA mass spectra is
shown by Pearson’s R² values larger than 0.90 for experiments with low organic mass
concentrations between 1.2 and 18 µg m-3 at an OH exposure of 4 × 107 cm-3 h, corresponding
to about two days of oxidation time in the atmosphere, based on a global mean OH
concentration of ~ 1 × 106 cm-3. α-Pinene SOA is more oxygenated at low organic mass
loadings. Because the degree of oxygenation influences the chemical, volatility and
hygroscopic properties of ambient aerosol, smog chamber studies must be performed at near-
ambient concentrations to accurately simulate ambient aerosol properties.
5.1 Introduction
Organic aerosol (OA) represents 20 to 90 % of the submicron atmospheric aerosol (Jimenez et
al., 2009 and references therein) and has numerous sources. It can be introduced directly by
combustion and mechanical processes into the atmosphere as primary organic aerosol (POA)
or can be formed by condensation of gas-phase reaction products with low vapor pressures
resulting in secondary organic aerosol (SOA). Modeling of SOA formation and aging
5.1 Introduction 27
processes requires accurate prediction of both SOA mass concentration and composition.
While traditional models underestimated the SOA burden (Volkamer et al., 2006) prediction
of SOA mass has recently been improved through the use of the volatility basis set framework
(Donahue et al., 2006; Robinson et al., 2007) although the system remains significantly
underdetermined (Hodzic et al., 2010). In contrast, efforts to reproduce ambient SOA
oxygenation levels using atmospherically relevant OH concentrations have been largely
unsuccessful. Here we explore the factors governing the degree of oxygenation of α-pinene
SOA produced via photooxidation in smog chamber experiments.
Analysis of aerosol mass spectrometer (AMS) data using the positive matrix factorization
(PMF) source apportionment method allows the total OA to be represented as a linear
combination of factors representing various sources and/or processes. The SOA fraction is
often represented in terms of semi-volatile oxygenated OA (SV-OOA) and low-volatility
oxygenated OA (LV-OOA) (Ulbrich et al., 2009; Jimenez et al., 2009; Metzger et al., 2010).
In addition to their volatility difference, SV-OOA has a lower atomic oxygen-to-carbon
(O : C) ratio (~ 0.25–0.6) than LV-OOA and often represents fresh aerosol closer to the
source, while LV-OOA, with a higher O : C ratio (~ 0.6–1.0) represents more aged OA (Ng et
al., 2010; DeCarlo et al., 2010; Lanz et al., 2010; Jimenez et al., 2009).
Two AMS mass fragments previously shown to be useful in describing atmospheric SOA
occur at m/z 44 (mostly particulate CO2+, with a minor contribution of C2H4O
+) and m/z 43
(mostly C2H3O+ for SOA, with a lesser contribution from C3H7
+). The f44 value, being the
ratio of the organic fraction of m/z 44 to total organics, has been empirically related to the
atomic O : C ratio for ambient measurements and is in large part derived from carboxylic
acids, of which a larger fraction is found in more aged aerosols (Aiken et al., 2008; Duplissy
et al., 2011). The ratio of organic m/z 43 to total organics (f43) is more closely related to
fragmentation of aldehydes, ketones and alcohols. The organic mass fractions in unit mass
resolution f44and f43are approximations for those in high resolution, being the organic mass
fractions of particulate CO2+ (f pCO2
+) and of C2H3O+ (f C2H3O
+). The f44 and f43 values
observed in ambient LV-OOA and SV-OOA factors obtained by PMF analysis of 43 ambient
datasets (Ng et al., 2010) typically fall within a triangular space. LV-OOA has high f44 and
low f43, while SV-OOA has lower f44 and a range of f43 values. The same triangle has been
transferred to high-resolution data within the Van Krevelen space (H : C vs. O : C) (Van
Krevelen, 1950; Ng et al., 2011a; Heald et al., 2010). SOA produced in smog chamber (SC)
studies typically falls within the range of ambient SV-OOA, almost always showing lower
degrees of oxygenation than ambient LV-OOA (Ng et al., 2010), with only a few exceptions
28 5 The link between organic aerosol mass loading and degree of oxygenation
(Bahreini et al., 2005; Chhabra et al., 2011). These mass spectral differences suggest that SC
SOA evaporates at lower temperatures than ambient LV-OOA. Although volatility is not
directly measured in most studies, Huffman et al. (2009) showed that SC SOA is typically
more volatile than ambient SOA. SOA from various non-biogenic pure precursors can reach
high degrees of oxygenation, although having higher or lower f43 values than ambient. In an
α-pinene oxidation flow reactor experiment f44 values as high as 0.25 were reached; however
these required OH concentrations that were orders of magnitude higher than in smog
chambers (Ng et al., 2010). Not only volatility but also hygroscopicity was related to the
atomic O : C ratio (Duplissy et al., 2011; 2008). More oxygenated particles take up more
water at a given relative humidity, suggesting increased cloud formation potential.
Measurements of dark α-pinene ozonolysis in a continuous-flow chamber by Shilling et al.
(2009) demonstrated that the aerosol chemical composition depends on the total organic mass
concentration; however the generated aerosol was less oxygenated than ambient LV-OOA.For
non-wall-loss-corrected organic mass loadings between > 140 µg m-3 and 0.5 µg m-3, O : C
values increasing from 0.29 to 0.45 and H : C values decreasing from 1.51 to 1.38 were
reported. Recently, LV-OOA-like aerosol was obtained in a smog chamber, but mostly by
starting with oxygenated gas-phase precursors (Chhabra et al., 2011), whereas most primary
volatile organic compound emissions are thought to be more hydrocarbon-like. However,
these results indicate that the location of SOA in the f pCO2+ - f C2H3O
+ as well as in the Van
Krevelen space is affected by precursor identity. Chhabra et al. (2011) showed O : C ratios for
α-pinene photooxidation of approximately 0.3–0.4 for organic mass concentrations of 54–
64 µg m-3 and OH exposures of 1.7–3.3 × 107 cm-3 h.
Three recent studies performed in flow reactors found SOA from α-pinene photooxidation
falling to the range of LV-OOA (Lambe et al., 2011; Massoli et al., 2010; Kang et al., 2011).
When high OH concentrations (e.g., 2 × 109 to 2 × 1010 cm-3 in Lambe et al. (2011)) are
produced in flow reactors, the probability that a low-volatility reaction product collides with
an OH radical and reacts further before it collides with a particle and condenses as SOA is
enhanced. Thus, the accelerated chemistry may lead to a different set of products, while
inhibiting slower condensed-phase reactions. Therefore the importance of heterogeneous
reactions may also be enhanced; Slowik et al. (2012) found that heterogeneous reactions at
OH exposures of 3 × 108 cm-3 h are sufficient to transform ambient biogenic aerosol to an
LV-OOA-like composition.
5.2 Method 29
The inability of smog chambers to generate α-pinene SOA with oxygenation, volatility and
(potentially) hygroscopicity similar to ambient LV-OOA could be an important gap in the
current understanding of ambient SOA. In this paper, results from an experimental study
using α-pinene, being, among other biogenic organic gases, an atmospherically relevant
precursor for SOA, are presented. The high non-fossil SOA fraction together with a high
contribution of monoterpenes to SOA in Marseille in summer time indicates that biogenic
VOC are important SOA precursors (El Haddad et al., 2013). The aim of this study is to find
the main driving factors responsible for the inability of smog chamber studies to yield LV-
OOA-like aerosol from the biogenic precursor α-pinene, even after the equivalent of tens of
hours of atmospheric aging. OH exposures of 3–14 × 107 cm-3 h were reached, which is
higher compared to the studies of Ng et al. (2011a) and Chhabra et al. (2011), but less than in
typical flow reactor studies.
5.2 Method
5.2.1 Experimental setup
Nine experiments (see Table 5.1) were carried out in the smog chamber (SC) of the Paul
Scherrer Institute (PSI): a 27 m³ Teflon bag suspended in a temperature-controlled wooden
housing. Four xenon arc lamps (4 kW rated power, 1.55 × 105 lumens each, XBO 4000
W/HS, OSRAM) were used to simulate the solar light spectrum. In addition, in seven of the
nine experiments 80 UV lights (Philips, Cleo performance 100 W) located underneath the SC
bag were illuminated to accelerate the aging process. The smog chamber housing is covered
inside with a reflective aluminum foil to maintain light intensity and light diffusion. A
comprehensive description of the PSI smog chamber is available in Paulsen et al. (2005).
During all experiments, photooxidation of the biogenic precursor α-pinene led to secondary
aerosol formation and growth. In general, experimental conditions were adjusted using the
following sequence: humidification of the chamber, addition of seed aerosol if applicable,
introduction of SOA precursor, addition of OH precursor, addition of NOx if applicable,
mixing period, turning-on of xenon and/or UV lights to generate OH radicals followed by a
reaction time of 5 to 22 h. The procedure for each individual experiment is described in Sect.
5.2.2.1 and summarized in Table 5.1.
30 5 The link between organic aerosol mass loading and degree of oxygenation
Table 5.1. Overview of experiment conditions. Org max (wlc) is the wall-loss-corrected organic mass concentration at the end of the experiment. Radiation sources are UV or xenon (Xe) lights. The OH tracer butanol-d9 is abbreviated with but-d9. Black carbon (BC) and NH4HSO4 represent seed aerosol in experiment 7.
Expt. Initial Org max RH NO NO2 Radiation Added
no. α-pinene (wlc) av(sd) av(sd) av(sd)* source(s)
[ppb] [µg m-3] [%] [ppb] [ppb]
1 7 4.5 50(1) 3.9(0.6) 4.9(1.8) UV+Xe HONO 2 14 17.9 48(2) 3.0(0.4) 5.9(0.9) UV+Xe HONO
3 20 6.2 40(2) 0.3(0.1) 0.8(0.3) UV+Xe HONO but-d9 SO2
4 22 1.8 44(1) 4.2(0.9) 20.0(9.9) UV+Xe HONO but-d9 SO2 NO
5 23 9.2 47(2) 0.6(0.9) 6.9(0.3)* UV+Xe but-d9 NO2
6 44 42.1 44(2) 0.3(0.8) 19.0(0.4)* Xe but-d9 O3 NO2 7 45 97.2 28(2) 1.0(0.2) 3.6(1.3) UV+Xe HONO BC & NH4HSO4 8 46 78.3 49(1) 2.0(1.1) 22.0(12.0) Xe HONO 9 50 66.2 47(3) 1.8(0.3) 9.0(3.0) UV+Xe HONO
*Initial NO2 addition that decayed to zero during experiments 5 and 6.
5.2.1.1 Introduction of particle and gas-phase reactants into the chamber
Liquid-phase α-pinene (98 %, Aldrich) and optionally the hydroxyl radical (OH) tracer (9-
fold deuterated butanol, 98 %, D9, Cambridge Isotope Laboratories), hereafter referred to as
butanol-d9, were sequentially injected with a syringe into an evaporation glass bulb heated to
80 °C. The two gas-phase compounds were carried with dilution and flush flows into the bag
(each 15 L min-1, maintained for 15 min) from an air purifier (737-250 series, AADCO
Instruments, Inc., USA), further referred to as “pure air”. The experiments were carried out at
40–50 % relative humidity (RH), except experiment 6, where the prevailing RH was
28 ± 2 %. The temperature (T) varied within a range of 21 °C to 24 °C between experiments.
Three NOx sources (HONO, NO and NO2) were added either in combination or separately
during the different experiments. Table 5.1 provides an overview of the initial α-pinene
concentrations, maximum wall-loss-corrected (wlc) organic mass concentrations, RH, initial
NO2 concentration before lights were switched on, average NO and NO2 concentrations
during the experiments, the radiation source(s) and the seed added.
HONO was used as a source of both NO and OH, except for experiments 5 and 6. It was
produced by continuous mixing of sodium nitrite (NaNO2, 1–3 mmol L-1) and sulfuric acid
(H2SO4, 10 mmol L-1) solutions in a reaction vessel by means of a peristaltic pump (Taira and
Kanda, 1990). The HONO product was entrained in 2.3–2.7 L min-1 pure air depending on the
experiment. Before lights on, 1–5 ppbv ( ± 10 %) of HONO was injected to provide NOx and
5.2 Method 31
enable photochemistry immediately after lights on (Initial concentrations: See supplementary
material Table S 5.1). The injection continued throughout the experiments to maintain a
similar NO concentration level.
In experiments 5 and 6, NO2 served as the NOx source, with 6.9 ± 0.7 ppbv and
19.0 ± 1.9 ppbv NO2 (purity: 98 %; 1005 ppmv ± 3 %), respectively, injected before lights on.
During experiment 4, NO (99.8 %; 1005 ppmv ± 2 %) was continuously injected in addition
to HONO, and the flow was decreased stepwise from 10.0 to 3.8 mL min-1 (0.37 to
0.14 ppbv min-1), which resulted in a slower increase of NO2 and a constant level of NO in the
chamber.
Before switching on the lights during experiment 7, a suspension of 50 µL L−1 black carbon
(printer ink, Tokai carbon, Japan) containing black carbon and a solution of 4 g L−1
ammonium hydrogen sulfate (NH4HSO4), both in water, were sequentially nebulized and
introduced into the chamber with 0.6 L min−1 and a dilution flow of 10 L min−1 to act as seed
particles. During experiments 3 and 4, 50 pptv SO2 (99.98 %; 502 ppmv ± 2 %) was injected
to photochemically produce H2SO4 nucleation, providing an aerosol surface rapidly and thus
accelerating SOA formation (Metzger et al., 2010). In experiment 6, eight hours after lights
on, 123 ± 4 ppbv of O3 were added to the existing concentration of 41 ± 1 ppbv to investigate
whether this would accelerate oxidation compared to the earlier period of the experiment. To
minimize SOA formation by -pinene ozonolysis, the injection was performed only after
99 % of the α-pinene had reacted.
Once all initial gas- and aerosol-phase components were present in the bag, a 20 to 30-min
mixing period was allowed before the lights were switched on. After each experiment the
smog chamber was cleaned by the injection of several ppmv of ozone for 5 h and irradiation
for 10 h with UV lights at 20 °C, followed by a flushing period with pure air and high relative
humidity (~ 70 %) at 30 °C for at least 20 h.
To ensure that the organic matter (OM) formed during the experiments is not significantly
influenced by background contamination in the smog chamber, blank experiments before,
during and after the campaign were carried out. The conditions of the five blank experiments
are listed in Table S 5.2 in the Supplement. During two blank experiments (B1 and B2) at RH
≈ 50 % with neither HONO nor seed aerosol present, the maximum mass concentration
measured by the SMPS was 0.16 µg m-3 and 0.03 µg m-3 after 5 h and 8 h exposure to UV and
xenon lights, respectively. A blank experiment (B3) with 6.6 ± 0.2 µg m-3 ammonium sulfate
((NH4)2SO4) seed, 10 ppbv HONO and a relative humidity of 61 ± 6 % yielded a peak organic
32 5 The link between organic aerosol mass loading and degree of oxygenation
mass concentration of 1.7 ± 0.1 µg m-3 30 min after lights on. A second and third seeding
period 1 h and 2 h after lights on resulted in a slight increase in the organic mass
concentration. Two additional seeded blank experiments (B4 with NO and B5 with HONO)
with a lower (NH4)2SO4 concentration yielded only 0.1–0.16 µg m-3 organic mass
concentration. The significantly higher background concentration in blank experiment B3 can
be explained by the contamination of the (NH4)2SO4 seed solution with organic compounds.
There is evidence that primary organic aerosol (~ 0.3 µg m-3) was injected with the seed. In
addition, it is likely that water-soluble organic compounds are injected with the aqueous seed,
which are then oxidized in the gas phase and form additional SOA. Moreover, the yield of
secondary organic mass is enhanced by the surface provided by the seed. Condensation occurs
earlier in the seeded blank experiments than for the unseeded blanks, where higher vapor
pressures are required for nucleation. Experiment 7 (which is most similar to the seeded blank
experiment) included a concentration of 69.2 µg m-3 and thus an organic mass concentration
well above the blank value. The organic mass concentration of the unseeded experiments is
well above that of the blank experiments B1, B2, B4, and B5.
In general, it is difficult to quantify the contribution of contaminants in the smog chamber to
the total organic aerosol mass over the course of an experiment. We estimate the time
evolution of contaminant mass using the multi-linear engine (ME-2, Paatero et al. (1999)), as
implemented in Igor Pro (Wavemetrics, Inc.) by Canonaco et al. (2013) ME-2 represents the
mass spectral time series recorded during the experiment as a linear combination of statistic
factor mass spectra and their time-dependent intensities, while allowing some or all of the
factor spectra to be constrained using a priori information. In this case, contaminant mass
spectra were constrained (a-value: 0) using one of the three selected spectra collected during
the blank experiment B3, while two additional left free. One hundred twenty iterations (40 for
each mass spectrum after the first, second and third seeding period, representing three
different aging times and chemical compositions) of the model using different randomly
distributed initial values resulted in a contribution of the constrained blank MS between 6.6
and 9.9 % in the first two hours to between 10 and 20 % in the last three hours of experiment
4 with the lowest organic mass concentration. A detailed description of the model runs and
results can be found in the Supplement (Figure S 5.1).
Another indication that the low-concentration experiments are not dominated by the
background contamination is shown in Figure S 5.2 of the Supplement. The chemical
composition of SOA in blank experiment B3 measured by the AMS differs from that
measured during the low-concentration experiments of the study as shown by their different
5.2 Method 33
location in the Van Krevelen space (H : C vs. O : C). We conclude that only experiment 4
with the lowest organic mass concentration in this study is impacted by a non-negligible
amount of contaminants from the smog chamber system.
5.2.1.2 Instrumental setup
Various instruments were used to monitor gas and aerosol properties in the PSI smog
chamber. A high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS,
Aerodyne Research, Inc., Billerica, MA, USA) was operated online to measure the chemical
composition (organics, ammonium, nitrate, sulfate, chloride) of non-refractory submicron
particles (DeCarlo et al., 2006). Because this instrument samples at a low flow rate
(0.1 L min-1), a supporting flow of ~ 3 L min-1 was maintained parallel to the AMS inlet to
minimize diffusive losses in the sampling lines. Gas-phase compounds with a higher proton
affinity than water (166.5 kcal mol-1) were measured with a proton transfer reaction mass
spectrometer (PTR-MS, Ionicon). Mass-to-charge ratios related to α-pinene (m/z 81 and m/z
137) and the OH tracer butanol-d9 (m/z 66) were analyzed in detail (see Sect. 5.2.2). A
chemiluminescence-based NOx instrument (Monitor Labs 9841A NOx analyzer) was attached
to the HONO source to monitor the injected concentration throughout the experiment. A
modified NOx instrument including a photolytic NO2-to-NO converter (Thermo
Environmental Instruments 42C trace level NOx analyzer) and two ozone monitors (Monitor
Labs 8810 ozone analyzer, Environics S300 ozone analyzer) monitored the gas phase in the
chamber. A scanning mobility particle sizer (SMPS, consisting of a TSI condensation particle
counter (CPC) 3022A and a TSI differential mobility analyzer (DMA) 3081) measured the
aerosol size distribution and a condensation particle counter (TSI CPC 3025A) the total
particle number concentration (diameter d > 3nm), respectively.
The unit mass and high-resolution data from the HR-ToF-AMS were corrected for
contributions from the gas phase. The contributions of multiple species to the same integer
m/z were deconvolved using a fragmentation-table-based approach (Allan et al., (2004);
Aiken et al., (2008)). The fragmentation tables were optimized for the current dataset, which
required changes at m/z 14, 36, 39, 40, 46, 47, 48, 64, 65, 80, 81, and 98, as discussed in the
Supplement (see Table S 5.3).
The total organic mass concentration was derived using the chemical composition (organics,
ammonium, nitrate, sulfate, chloride) measurements from the HR-ToF-AMS and the total
34 5 The link between organic aerosol mass loading and degree of oxygenation
volume measured with the SMPS. The ratio of SMPS to HR-ToF-AMSvolume, after applying
compound-specific densities, results in a correction factor applied to the measured HR-ToF-
AMS organic mass concentration (details in the Supplement). The data were further corrected
for wall losses, as described in Sect. 5.2.3.
5.2.2 Estimation of OH exposure
Depending on the design of smog chamber experiments, the OH concentration and thus the
photochemical age of the reaction system can vary considerably between experiments.
Furthermore, within a single experiment the photochemical age is not necessarily directly
proportional to the light exposure time. Therefore we here discuss reaction time in terms of
OH exposure (unit: cm-3 h), defined as the OH concentration integrated over time. This scale
is preferable when comparing the evolution of experiments, especially when observing
oxidation processes, as it is the chemically relevant aging time. In this study we determine
OH exposures combining two methods: an OH tracer method introduced by Barmet et al.
(2012) and a method based on the initial decay of the gas-phase precursor α-pinene.
5.2.2.1 OH tracer method
Via a heated glass bulb, 1.5 µL (corresponding to ~ 14.5 ppbv) of the OH tracer butanol-d9
(detected as M+H+-H2O at m/z 66) was injected into the chamber (Sect. 5.2.1.1). The OH
tracer was present during the last hour of experiment 5, the second half of experiment 6, and
for the entire lengths of experiments 3 and 4. Butanol-d9 is consumed by reaction with OH
and diluted by the HONO input described in Sect. 5.2.1.1 (we assume as a first approximation
a constant chamber volume (V)) following the reaction kinetics governed by Eq. (5.1):
butanol‐d9OH,butanol‐d9 ∙ OH ∙ butanol‐d9 ∙ butanol‐d9 , (5.1)
where kOH, butanol-d9 = 3.4 × 10-12 cm3 molecules-1 s-1, V represents the chamber volume
(27 m3), and fdil the dilution flow [m3 s-1].
OHexposure,
∙ ∆
∆d (5.2)
The slope of the temporal decay of ln(butanol-d9) at each time step was divided by the
reaction rate constant kOH, butanol-d9 and corrected for the dilution to derive the OH
5.2 Method 35
concentration at each time step. Integrating this term with time (Eq. (5.2)) results in the OH
exposure (Barmet et al., 2012).
5.2.2.2 α-Pinene method
Similar to the OH tracer decay, the decay of α-pinene can be utilized to derive the OH
concentration. Compared to the OH tracer method, limitations of this method are the more
rapid consumption of α-pinene and its simultaneous reaction with both OH and O3 as shown
by Eq. (5.3). The OH exposure was therefore derived from the decay of ln(α-pinene), while
correcting for the time-dependent reaction with O3 and, if present, for the dilution of the
chamber air due to the HONO input (described in Sect. 5.2.2.1) as shown in Eq. (5.4).
α‐pineneOH ∙ OH ∙ α‐pinene ∙ O ∙ α‐pinene ∙ α‐pinene , (5.3)
where kOH = 5.3 × 10-11 cm3 molecules-1 s-1 and kO3 = 8.9 × 10-17 cm3 molecules-1 s-1,
OHexposure ∙ ∆
∆∙ O d (5.4)
Only data fulfilling the criterion α-pinene ≥ 1 ppbv were used to ensure all measurements fell
well above the PTR-MS detection limit. After α-pinene decayed below 1 ppbv, the OH
concentration was assumed to be constant for the rest of the experiment time for experiments
with continuous HONO addition.
5.2.2.3 Application of the methods to the dataset
The two estimates of OH exposure were compared in experiments 3 and 4, where both α-
pinene and butanol-d9 were above detection limit throughout the experiment (Figure S 5.3,
Supplement). The methods agree within 20 % for later in the experiment, which shows that
the α-pinene method is valid at least for experiments with constant HONO input and thus a
constant source of OH radicals.
The α-pinene method was utilized to derive the OH concentration of experiments 7, 8 and 9
with constant HONO input and α-pinene above detection limit for at least 1.3 h. The OH
exposure from a repeat experiment using the butanol-d9 method was applied to experiments 1
and 2, conducted at substantially higher HONO/α-pinene ratios (0.2 and 0.4, respectively).
The fast decay of α-pinene within the first 30 min during those two experiments due to the
36 5 The link between organic aerosol mass loading and degree of oxygenation
high accumulated HONO concentration before lights on and off-gassing from the walls after
lights on, as previously measured by Metzger et al. (2008), gives rise to an overestimation of
the OH exposure when using the α-pinene method. This is due to the assumption of a constant
OH concentration once the α-pinene is consumed. The repeat experiment shows the same
characteristics in the α-pinene decay, with the advantage of having the OH tracer butanol-d9
present for the whole experiment. A comparison of the three experiments is shown in Figure
S 5.4 of the Supplement. By applying the OH exposure of the repeat experiment to
experiments 1 and 2, an overestimation of the OH concentration later in the experiment could
be avoided.
In the course of experiments 5 and 6, the initially added NOx concentration decayed to very
low concentrations, causing a substantial change in the gas-phase chemistry including the
production rate of ozone and thus OH and the fate of peroxy radicals. An indication of
changes in chemistry is the change in the steepness of the ozone increase during the
experiments 5 (1.5 h after lights on) and 6 (5.5 h after lights on), once the NOx decayed to low
concentrations. One may assume that RO2 radicals react less with NO in this “low NOx”
regime and more with HO2 and RO2 forming e.g., peroxides. However there was no direct
measure of RO2 or peroxides available.
In experiment 6, the ozone leveled off before being increased artificially by the addition of
123 ± 4 ppbv of O3 eight hours after lights on. For those two experiments, OH exposures
derived from the α-pinene decay in the beginning and the decay of butanol-d9, added towards
the end of the experiment, were merged. The mean OH concentration in the smog chamber
was indirectly determined by dividing the OH exposure by the respective time period. The
highest OH concentration was 5 × 107 cm-3 and occurred at the beginning of experiments 1
and 2. On average, the OH concentrations during the experiments were in the range of 0.12–
2.7 × 107 cm-3. A compilation of the derived OH exposures is shown in Figure S 5.5 in the
Supplement. When comparing experiments utilizing the α-pinene-derived OH exposure, note
that the OH concentration is assumed to be constant after the drop below the threshold of
1 ppbv α-pinene. This extrapolation leads to uncertainties of the α-pinene derived OH
exposure, which increases with experiment time. Nevertheless these uncertainties do not alter
the main outcome of the study.
5.3 Results 37
5.2.3 Wall loss correction
The measured aerosol mass concentration in the smog chamber is the net result of mass
produced in the chamber and mass lost to the walls. Wall loss rates were determined from a
period near the end of the experiment where chemical changes to the aerosol have slowed to
the point that wall losses are expected to be the dominant factor controlling changes in the
measured particle mass. The measured (AMS) aerosol mass during this period was fitted with
an exponential. The data were then corrected by dividing the measured organic mass
concentration by the exponential decay (see Figure S 5.6 in the Supplement). The estimated
half-lives ranged between 2.8 and 10 h, the maximum derived from experiment 8, with a very
short period to fit. Selecting a period when minor mass production is still possible leads to a
lower limit for the wall loss correction assuming no major fragmentation due to the UV light
exposure and no major loss of vapors to the walls. This may lead to some underestimation of
the aerosol loading, which however is difficult to quantify.
5.3 Results
5.3.1 General reproducibility of the aerosol degree of oxygenation
The vaporization and ionization processes in the AMS fragment the sampled aerosol
compounds. As described in the Introduction, the fraction of particulate CO2+ (f pCO2
+) and
the corresponding organic mass fraction f44 (defined as the organic signal at m/z 44
normalized to the total organic mass) are related to carboxylic acids and proportional to the
atomic O : C ratio, whereas the fraction of fragment C2H3O+ (f C2H3O
+) and the corresponding
organic mass fraction f43 are related to aldehydes, ketones and alcohols. The higher the O : C,
the more oxygenated the aerosol. The f44-f43 space was used to separate the two factors LV-
OOA and SV-OOA (Ng et al., 2010) and is used here in Figure 5.1a and Figure 5.1b to
describe the chemical evolution of aerosol derived from α-pinene photooxidation in this
study. Figure 5.1a shows 30-min averages of f pCO2+ vs. f C2H3O
+ from high-resolution data,
while Figure 5.1b compares 30-min averaged data of this study with other studies (Chhabra et
al., 2011; Kang et al., 2011; Lambe et al., 2011) in the f44-f43 space with each of the
experiments marked by a different symbol. The legend in Figure 5.1a gives the final organic
mass concentration reached in each experiment after wall loss correction. Despite varying
38 5 The link between organic aerosol mass loading and degree of oxygenation
organic mass concentrations, OH concentrations, NOx concentrations and RH in the smog
chamber (see Table 5.1), all experiments are located within the same region on the right-hand
side of the triangle originating from ambient data (Ng et al., 2010). Experiment 6, 7 and 8
show an initial decrease in f pCO2+due to the condensation of early-generation semi-volatile
organic compounds, as shown previously in Baltensperger et al. (2005). During the ongoing
oxidation reactions in the smog chamber more highly oxygenated products are formed,
resulting in an increased f pCO2+ together with a decreased f C2H3O
+. This causes movement
from the lower right to the upper left in Figure 5.1a and Figure 5.1b with increasing OH
exposures, indicated by the arrows. Together with e.g., SOA from wood burning, which is
found on the left-hand side (Heringa et al., 2011), the mixture of aerosol from several sources
can explain a wide range of the empirically derived triangle. The three arrows indicating
f pCO2+ - f C2H3O
+ pairs at the same OH exposure are explained in Sect. 5.3.2.
5.3 Results 39
Figure 5.1. (a) Thirty-minute averages (except expt. 4: 60min) of f pCO2+ vs. f C2H3O
+ color coded for the nine experiments. The legend shows the final wall-loss-corrected organic mass concentration at the end of each experiment. The three arrows indicate the f pCO2
+ - f C2H3O+ pair when an OH exposure of
3.5 × 107 cm-3 h is reached for selected experiments (4, 3, 6). Dashed lines represent the observed range of ambient SOA (Ng et al., 2010). (b) Unit mass resolution organic mass fraction f44 vs. f43 color coded for the nine experiments. For comparison, environmental chamber (Chhabra et al., 2011) and flow reactor data (Kang et al., 2011; Lambe et al., 2011) of α-pinene photooxidation experiments are shown and color coded by the OH exposure.
Figure 5.1b shows the organic mass fractions f44 vs. f43 in unit mass resolution for the nine
experiments of this study compared to α-pinene photooxidation studies in three other systems.
Next to the color code by experiment number of this study, the data of Kang et al. (2011),
Lambe et al. (2011) and Chhabra et al. (2011) are color coded with the OH exposure. Chhabra
et al. (2011) measured in an environmental chamber (Caltech dual 28 m³ Teflon laboratory
chambers), while Lambe et al. (2011) and Kang et al. (2011) utilized flow reactors (Potential
aerosol mass chamber, Kang et al., 2007) for their experiments. Chhabra et al. (2011) show
slightly lower f44 and higher f43 at organic mass concentrations of 64 and 54 µg m-3,
respectively, while the experiments were performed at much lower RH (4.2 %; 4.9 %) and
with different OH precursors (H2O2; CH3ONO) and NOx concentrations (0; 800 ppbv)
present. In the study of Kang et al. (2011) the organic mass concentrations (90–110 µg m-3)
40 5 The link between organic aerosol mass loading and degree of oxygenation
are similar to the high-concentration experiments in this study and for low OH exposures, and
the location in the f44-f43 space is comparable. For higher OH exposures, the oxidation process
continues on a similar slope as in this study, indicating further aging. Lambe et al. (2011)
showed comparable pairs of f44-f43 for low OH exposures, while for higher OH exposures
much higher f44 was found, which the authors suggested to be due to the loss of mass after
fragmentation in the particle takes place, seen by shrinking particles for higher OH exposures
(Fig. S2, Lambe et al., 2011).
Thus, for the first time, an organic mass fraction f44 as high as many ambient LV-OOA and
well above the SV-OOA range is obtained from an α-pinene photooxidation smog chamber
study at ambient-like OH concentrations.
Figure 5.2 shows the Van Krevelen diagram (H : C vs. O : C) of the nine experiments (30-min
averaged data, except expt. 4: 60-min average). The relationship between f44and O : C, as well
as f43 and H : C is shown in Figure S 5.7a and Figure S 5.7b for data of this study. The
diagram allows for interpretation of changes in functionality (slope -2: aliphatic → carbonyl
functionality; slope 0: aliphatic → alcohol or peroxide functionality; slope -1: addition of
carboxylic acid functionality). Heald et al. (2010) found an average slope of -1 for bulk
atmospheric and laboratory OA. The ongoing oxidation in the nine experiments results in an
increased O : C together with a decrease in H : C, seen in a movement from the upper left to
the lower right in the figure. All experiments fall within the range of ambient data indicated
by the dashed lines (Ng et al., 2011a) and follow a slope of roughly between -1 and -2,
indicated by the solid lines.
5.3.2 Dependence of degree of oxygenation on the organic mass concentration
Figure 5.1a shows three arrows pointing to f pCO2+ - f C2H3O
+ pairs at the same OH exposure
of 3.5 × 107 cm-3 h (averaged ± 15 min), isolating the effect of organic mass concentration for
three selected experiments (expt. no. 3, 4, 6) during which the OH tracer butanol-d9 was
present in the chamber for most of the experiment. The respective OH exposures were derived
according to the methods described in Sect. 5.2.2. The organic mass concentrations (wlc,
averages and standard deviation for ± 15 min, except expt. 4: 60 min) at this OH exposure in
experiments 6, 3 and 4 were 42.3 ± 0.6 µg m-3, 5.8 ± 0.2 µg m-3 and 1.7 ± 0.1 µg m-3,
respectively.
5.3 Results 41
Figure 5.2. Van Krevelen diagram (H : C vs. O : C ratio) of the nine experiments together with the observed range of ambient SOA represented by dashed lines. The data are averaged over 30 min (except expt. 4: 60 min).
The corresponding averaged f pCO2+ values were 0.106 ± 0.001, 0.131 ± 0.002 and
0.140 ± 0.014, respectively. Seen by the differences in f pCO2+ for the three different mass
loadings, the data clearly show that at the same OH exposure, the degree of oxygenation is
dependent on the total organic mass concentration present in the chamber.
For a comprehensive comparison of all experiments described in this study, the OH exposure
was utilized as the aging scale, rather than the time after lights on. The evolution of O : C as a
function of organic mass concentration (wlc), both averaged for 10 min, is shown in Figure
5.3 with each of the nine experiments marked by a different symbol and color-coded by the
OH exposure. Initially, there is a period of rapid mass increase with a slow increase in O : C,
followed by a later period of a continuous O : C increase with only a slight further increase in
mass. The precise rate and termination point of the late-experiment mass increase are
somewhat uncertain due to corresponding uncertainties in the applied minimum wall loss
correction method (Figure S 5.6, Supplement).
42 5 The link between organic aerosol mass loading and degree of oxygenation
Figure 5.3. O : C ratio as a function of the organic mass concentration (µg m-3) in the chamber for the nine experiments. The color code indicates the OH exposure. Thirty-minute mean values at selected OH exposures are represented by colored squares (except expt. 4: 60-min average). The colored lines represent linear least orthogonal distance fits between O : C and org (wlc) at three selected OH exposures with a mean slope of (0.07 ± 0.01) % m3 µg-1.
The initial period is likely governed by condensation of early-generation, semi-volatile
products and their condensation therefore yields a low increase in O : C. As aging proceeds,
the gas-phase organics become more oxidized and thus more oxygenated (higher O : C)
compounds condense. Additional aging of the particles is possible through repartitioning of
semi-volatile condensed-phase OA to the gas phase, followed by gas-phase oxidation and re-
condensation of the oxygenated products. This process also increases O : C, while only
slightly affecting the total OA mass. Therefore, partitioning is more strongly affected by the
significantly varying mass concentrations between the nine experiments than the slight mass
increase within a given experiment. Higher OA mass correspond to increased condensation of
semi-volatile compounds, while low-volatility compounds occur in the particle phase even at
low concentrations (Donahue et al., 2006). Ng et al. (2010) also suggest that more oxygenated
5.3 Results 43
compounds tend to be less volatile. The reaction of less oxygenated, semi-volatile compounds
with OH proceeds in the gas phase until either (1) they become sufficiently oxygenated to
condense (which requires a higher level of oxygenation than at high mass concentrations) or
(2) they fragment sufficiently such that they will not enter the particle phase. Both pathways
lead to an increase in the net O : C for experiments conducted at low OA concentrations.
In Figure 5.3 the color-coded squares correspond to average O : C ratios and OA mass
concentration (wlc) at OH exposures of 2.5, 4, 6, 8 and 11 × 107 cm-3 h. Averages were
calculated as ± 15 min from the given OH exposure, except for expt. 4, where a ± 30-min
average was calculated. Linear (least orthogonal distance) fits of O : C as a function of OA
mass concentration at 2.5, 4 and 6 × 107 cm-3 h OH exposure are shown by the lines in the
corresponding color. Table 5.2 presents 30-min averages (except expt. 4: 60-min) of O : C
and organic mass concentration (wlc) for the five different OH exposures. The significant
dependence of O : C on the organic mass is shown by the slope ∆O : C/∆org (wlc), on average
(0.070.01) % m3 µg-1, with slopes and intercepts listed in Table 5.3.
Table 5.2. Thirty-minute averages of O : C and wall-loss-corrected organic mass concentration in µg m-3, org (wlc) at the given OH exposures. The data are displayed in Figure 5.3.
OH exposure [× 107 cm-3 h]
2.5 4 6 8 11 Expt. no.
O:C Org
(wlc) O:C
Org (wlc)
O:C Org (wlc)
O:COrg (wlc)
O:COrg (wlc)
1 0.54 3.2 0.60 4.4 0.62 4.5 0.64 4.6 0.66 4.5 2 0.54 15.6 0.56 18.1 0.59 18.0 0.61 18.0 0.65 18.0 3 0.52 6.0 0.54 5.7 0.53 5.5 0.54 5.7
4* 0.51* 1.5* 0.55* 1.6* 0.54* 1.7* 5 0.52 9.1 6 0.46 41.5 7 0.49 92.9 0.51 97.3 8 0.45 77.8 0.47 78.2 9 0.49 62.2 0.51 65.3 0.53 65.3
*Data are 60-min averages
44 5 The link between organic aerosol mass loading and degree of oxygenation
Table 5.3. Slopes and intercepts of linear (least orthogonal distance) fits between O : C and org (wlc). Fit lines are shown in Figure 5.3 with the OH exposure as color code.
OH exposure [× 107 cm-3 h]
O:C = a+b·org (wlc) 2.5 4 6
a 0.53 ± 0.01 0.57 ± 0.01 0.57 ± 0.02
b [m3 µg-1] -0.00071 ± 0.00022 -0.00084 ± 0.00027 -0.00056 ± 0.00079
This implies that at typical atmospheric concentration levels, partitioning effects on SOA
oxygenation are highly sensitive to the organic mass concentration. Using typical atmospheric
organic mass concentrations in smog chamber studies is not only crucial to reproduce the
volatility and degree of oxygenation of ambient SOA but also to accurately determine cloud
condensation nuclei activity due to the dependence of the hygroscopicity on the O : C ratio
(Duplissy et al., 2011). Ng et al. (2011b) found an even stronger dependence of O : C on the
organic mass concentration (0.55 % m3 µg-1) of ambient data with an unknown distribution of
OH exposures (possibility of low OH exposure for high OA mass and high OH exposure for
low OA mass).
5.3.3 Dependence of degree of oxygenation on the OH exposure
The degree of oxygenation reached by α-pinene SOA depends on both the organic mass
concentration (discussed above) and the OH exposure. For each experiment, the slope of
∆O : C/∆(OH exposure) was fitted (least orthogonal distance fit) for the part of the
experiment dominated by aging (rather than mass production), defined as the period after the
peak of suspended organic mass concentration was reached in the chamber. The individual
slopes are shown in Figure S 5.8 and summarized in Table S 5.4 in the Supplement. An OH
exposure between 3 and 25 × 107 cm-3 h is needed to increase O : C by 0.05.
Table 5.4 shows OH exposures (and corresponding organic mass concentrations (wlc))
required to obtain O : C > 0.6, a typical lower limit value for LV-OOA. For experiments
during which this threshold of 0.6 was not reached, the derived slopes of ∆O : C/∆(OH
exposure) and intercepts were utilized to estimate the total OH exposure needed to do so. The
OH exposure observed for oxidation of SOA to an O : C value of ~ 0.64 in the Mexico City
5.3 Results 45
plume (~ 4–5 × 107 cm-3 h, 6 h air transport time) as estimated from aircraft measurements
(DeCarlo et al., 2010; Dusanter et al., 2009) is, despite different precursors, on the lower edge
of the range of OH exposures required in this study.
Table 5.4. The OH exposure required to increase the O : C ratio above 0.6 at the corresponding organic mass concentration org (wlc). For experiments that do not exceed the threshold of 0.6, the OH exposures are extrapolated and the maximum measured org (wlc) is given, both indicated by the asterisk.
Expt. no. OH exposure org (wlc) [107 cm-3 h] [µg m-3] 1 4.7 4.4 2 7.0 18.1 5 7.2* 9.2* 7 9.7* 97.2* 6 11.6* 42.1* 9 12.5* 66.2* 8 19.8* 78.3* 3 23.7* 6.2* 4 35.2* 1.8*
5.3.4 Classification of chemical composition using reference mass spectra
To relate the aerosol chemical composition found in this study to ambient data, the SC
organic mass spectra were compared to reference mass spectra retrieved from ambient
measurements. These reference spectra were obtained from PMF analysis of a number of
ambient datasets and compiled by Ng et al. (2011a) and are available on the AMS Spectral
Database (Ulbrich et al., 2009). Figure 5.4 shows R² values (Pearson correlation) of the LV-
OOA (filled circles) and SV-OOA (empty circles) unit mass spectra from (Ng et al., 2011a)
with unit mass spectra from this study as a function of wall-loss-corrected organic mass
concentration. For this comparison, all organic mass spectra are converted to be consistent
with the fragmentation table of Aiken et al. (2008). The mass spectra for each of the nine
experiments were averaged for 30 min surrounding the OH exposures of 2 × 107 cm-3 h and
4 × 107 cm-3 h, respectively (i.e., the selected exposure ± 15 min). All organic m/z calculated
as a constant fraction of m/z 44 in the fragmentation table (i.e., m/z 16, 17, 18, 19, 20 and 28)
were excluded from the correlation test to avoid overweighting of these ions. The general
trend for both exposures shows increased correlation with LV-OOA and decreased correlation
with SV-OOA for decreasing mass concentrations. For all mass concentrations, an increasing
46 5 The link between organic aerosol mass loading and degree of oxygenation
Figure 5.4. Squares of the Pearson correlation coefficients, R², of measured mass spectra in comparison with LV-OOA (filled symbols) and SV-OOA (empty symbols) reference spectra as a function of the organic mass concentration (wlc). The color code represents the OH exposure at the midpoint of a 30-min mass spectral average. The corresponding mass spectra are shown in Figure S 5.10 in the Supplement.
R² (LV-OOA) and a decreasing R² (SV-OOA) with increasing OH exposure is found. The
dependence on mass concentration occurs for the partitioning-related reasons discussed above
in conjunction with increased O : C for low mass concentrations, while the dependence on
OH exposure occurs because SOA spectra become more LV-OOA-like with photochemical
age. For the high-concentration experiments, the difference between R² (SV-OOA) and
R² (LV-OOA) is more pronounced for the lower OH exposure than for the higher OH
exposure. Nevertheless, the lower R² (LV-OOA) of the high-concentration experiments
compared to the low-concentration experiments even for the enhanced OH exposure suggest a
substantial difference in the chemical composition as a function of the organic aerosol
loading. The low-concentration experiments (organic mass < 20 µg m-³ in Figure 5.4)
correlate strongly with LV-OOA (R² > 0.9) for an OH exposure of 4 × 107 cm-3 h. This
indicates that for low organic mass concentrations, SOA from smog chamber α-pinene
photooxidation yields LV-OOA-like mass spectra after a sufficient oxidation time. Also for
5.4 Conclusions 47
higher OH exposures, the correlation to LV-OOA is very high (R² > 0.89) for the low-
concentration experiments, while the R² values with SV-OOA decrease dramatically (Figure
S 5.9, Supplement).
5.4 Conclusions
A series of smog chamber experiments were conducted to identify main reasons for the
discrepancy between ambient and smog chamber aerosol degree of oxygenation, which in
turn strongly affects aerosol volatility and hygroscopicity. In this study, the aerosol products
from α-pinene photooxidation are located on the right-hand side of the f44-f43 space bounding
the range of PMF factors previously identified in ambient SOA (Ng et al., 2010). The O : C
ratio, a proxy for the degree of oxygenation, is increasing with decreasing organic mass
loadings. This has been shown in a comparison of nine smog chamber experiments where the
OH exposure was estimated to isolate the effects of mass loading and photochemical age.
Similar dependencies of f44 on the precursor concentration have been shown previously for
other compounds than α-pinene, such asβ-caryophyllene (Alfarra et al., 2012).
We conclude that low (near-ambient level) organic mass loadings are required in order to
obtain oxygenation levels comparable to those of the low-volatility oxygenated organic
aerosol (LV-OOA) PMF factors retrieved in numerous field campaigns. An OH exposure
between 3 and 25 × 107 cm-3 h is needed to increase O : C by 0.05 during aerosol aging. This
study marks the first smog chamber production of LV-OOA-like SOA from the
atmospherically relevant precursor α-pinene. For ozonolysis of α-pinene, the degree of
oxygenation falls in the range of SV-OOA even at low concentrations (Shilling et al., 2009;
Ng et al., 2010). This is consistent with the hypothesis of Donahue et al. (2012) that further
aging occurs with OH after/together with ozonolysis. A correlation test between measured
SOA and reference LV-OOA (Ng et al., 2011a) aerosol mass spectra shows Pearson’s R²
values larger than 90 % for a sufficient OH exposure in the chamber in low mass
concentration experiments (~ 1.2–20 µg m-3). We suggest that smog chamber studies must not
only be performed at reasonable oxidant concentrations but also at near-ambient mass
concentrations to accurately simulate the chemical properties, volatility and hygroscopicity of
ambient aerosol.
48 5 The link between organic aerosol mass loading and degree of oxygenation
Acknowledgements. This work has been supported by the EU 7th Framework projects
EUROCHAMP-2 and PEGASOS, as well as the Swiss National Science Foundation. We
thank Rene Richter and Günther Wehrle for their technical support at the smog chamber, and
in addition Imad El-Haddad, Stephen Platt and Robert Wolf for discussions and their support
during the experiments.
5.5 Supplementary material 49
5.5 Supplementary material
Table S 5.1. Overview of HONO input into the smog chamber before switching on the lights. The last column contains the ratio between HONO and α-pinene initial concentrations.
Expt. initial HONO α-pinene HONO/α-pinene
no. ppbv ( ± 10 % instrument
accuracy) ppbv
1 1.6 7 0.2
2 4.9 14 0.4
3 1.0 20 0.05
4 1.0 22 0.05
7 1.9 45 0.04
8 2.8 46 0.06
9 5.1 50 0.1
50 5 The link between organic aerosol mass loading and degree of oxygenation
Table S 5.2. Conditions of blank experiments B1-B5. The SMPS mass concentration is only given for blank experiments without seed. Detection limit is abbreviated with DL.
Blank
no.
Maximum
Organic
mass
RH T NO NO2 radiation added Previous
av(sd) av(sd) av(sd) av(sd) source seed SC use
µg·m-3 % °C ppb ppb ppb µg·m-3
(B1)
SMPS: 0.03
(Suspended)
AMS: below
DL
Ca. 50* Ca. 22* 0.9(0.3) no
data UV+Xe - -
moped emissions
(up to
100 µg·m-3)
(B2)
SMPS: 0.16
(Suspended)
AMS: below
DL
49(2) 21.8(0.6) 1.0(0.3) Below
det.lim. UV+Xe - -
α-pin photooxid.
(2–73 µg/m³)
moped emissions
(up to
100 µg·m-3)
(B3) AMS: 1.7
(Suspended) 61(6)** 25.2(1.4) 3.3(0.6)
Below
det.lim. UV+Xe
HONO
10
(NH4)2SO4
(6.6 ± 0.2)
α-pin photooxid.
(1.4–80 µg·m-3)
(B4) AMS: 0.16
(wlc) 80-85 UV+Xe
NO
40***
(NH4)2SO4
(1.8)
α-pin photooxid.
(1.4–80 µg·m-3)
(B5) AMS: 0.11
(wlc) 80-85 UV+Xe
HONO
~ 2
(NH4)2SO4
(1.2)
α-pin photooxid.
(1.4–80 µg·m-3)
* During blank experiment B1, no radiation shielded T/RH measurement existed. 55 % RH
and 19.5 °C were measured in darkness before lights were switched on. Assuming the
temperature increases by 3 °C after lights are switched on, leads to a RH of 50 %.
** Before lights were switched on, 85 % RH and 19.2 °C were measured. After lights were
switched on, the temperature increased to 25 °C, resulting in a decreased RH of 60.9 %.
*** 40 ppbv of NO added to the blank before lights were switched on.
5.5 Supplementary material 51
Table S 5.3. Changes in unit mass resolution fragmentation table compared to Aiken et al. (2008).
m/z Expt. 7
(with NH4HSO4 seed)
Expt. 1-6; 8-9
(without NH4HSO4 seed)
Aiken et al. (2008)
(standard frag table)
Organics
14 3.84·frag_organic[13] (0.14-4.17)·
frag_organic[13]
16 0.107·frag_organic[17] 0.107·frag_organic[17] 0.25·frag_organic[17]
28 0.93·frag_organic[44] 0.93·frag_organic[44] 1·frag_organic[44]
30 0.16·frag_organic[29] 0.16·frag_organic[29] 0.022·frag_organic[29]
36 36,-frag_air[36] 36,-frag_air[36]
37 37 37 37,-frag_chloride[37]
38 38,-frag_air[38] 38,-frag_air[38] 38,-frag_chloride[38],-
frag_air[38]
39 5·frag_organic[38] 5·frag_organic[38]
40 40,-frag_air[40] 40,-frag_air[40]
46 0.025·frag_organic[44] 0.025·frag_organic[44]
47 47 47
48 4·frag_organic[62] 0.19·frag_organic[62] 0.5·frag_organic[62]
64 0.35·frag_organic[50]+
0·frag_organic[78]
0.07·frag_organic[50]+
0.03·frag_organic[78]
0.5·frag_organic[50]+
0.5·frag_organic[78]
65 0.55·frag_organic[51]+
0.15·frag_organic[79]
0.55·frag_organic[51]+
0.1·frag_organic[79]
0.5·frag_organic[51]+
0.5·frag_organic[79]
80 2·frag_organic[94] 1.1·frag_organic[94] 0.75·frag_organic[94]
81 0.4·frag_organic[67]+
0.25·frag_organic[95]
0.3·frag_organic[67]+
0.35·frag_organic[95]
0.5·frag_organic[67]+
0.5·frag_organic[95]
98 0.65·frag_organic[84]+
0.55·frag_organic[112]
0.5·frag_organic[84]+
0.7·frag_organic[112]
0.5·frag_organic[84]+
0.5·frag_organic[112]
air
14 14,-frag_nitrate[14],-
frag_organic[14]
14,-frag_nitrate[14],-
frag_organic[14]
14,-frag_nitrate[14]
52 5 The link between organic aerosol mass loading and degree of oxygenation
NH4
16 0.77·frag_NH4[17] 0.77·frag_NH4[17] 16,-frag_water[16],-
frag_air[16],-
frag_sulfate[16],-
frag_organic[16]
NO3
46 46,-frag_organic[46] 46,-frag_organic[46] 46
K
39 39,-frag_organic[39] 39,-frag_organic[39] 39
Correction for collection and transmission efficiency
The volumes derived from the two instruments SMPS and AMS were compared, applying the
following densities in g/cm³ to the AMS species: ρOrg=1.4; ρSO4=1.78; ρNO3=1.72; ρNH4=1.75;
ρChl=1.4. The AMS data were corrected by applying the following correction factors (CF) to
the organic mass concentration based on the ratio volumeSMPS/volumeAMS. Possible reasons
for a disagreement between SMPS and AMS are given in brackets.
CF=2.7 for experiment 1 (volume weighted dm = 60-70nm)
CF=1.5 for experiment 2 (volume weighted dm = 70nm)
CF= (1.0-1.2) for experiments 3, 4, 5, 6, 8, 9 (volume weighted dm=150-200nm)
CF=1.5 for experiment 7 (bouncing of sulfate)
For experiments 1 and 2, the volume weighted mean diameter is on the lower edge of the
AMS measurement range and therefore the AMS samples significantly less than the SMPS.
As all experiments except expt. 7 were nucleation experiments, the chemical composition is
not expected to vary substantially as a function of diameter, relevant for expt. 1.
5.5 Supplementary material 53
Table S 5.4. Slope of O : C/∆(OH exposure) for the period where aging dominates (see Figure S 5.8) and the OH exposure required to increase O : C by 0.05.
Expt. no. ∆O:C/∆(OH exposure) ∆OH exposure/∆O:C [10-9 cm3 h-1] [107 cm-3 h/0.05]
4 0.20 24.50
3 0.35 14.43
8 0.84 5.96
1 0.93 5.37
2 1.10 4.55
9 1.11 4.50
6 1.52 3.29
7 1.57 3.18
5 1.63 3.07
54 5 The link between organic aerosol mass loading and degree of oxygenation
Contribution of blank experiment B3 to experiment 4
We used the mass spectra (MS) measured after the first, second and third seeding period
during blank experiment B3, representing different aging times and thus chemical
composition, as input for the statistical tool ME-2 (multi-linear engine: model by Paatero et
al. (1999), analysis interface by Canonaco et al. (2013) to estimate its contribution to the total
organic mass concentration. For the ME-2 runs, the blank experiment mass spectrum was
fixed (a-value: 0) and two more free components were allowed (similar to the approach of
Lanz et al. (2007) for ambient measurements). 120 iterations (40 for each blank experiment
MS) of the model using different randomly distributed initial values resulted in an average
contribution of the constrained blank MS between 6.6–9.9 % in the first two hours up to 10–
20 % in the last three hours of experiment 4 with the lowest organic mass concentration. For
the model runs, the m/z range of 12–250 was used. 5 out of 40 iterations resulted in the
following time series and mass spectra. The spectrum of blank experiment B3 was fixed as
factor 1, shown in Figure 5.1a and Figure 5.1b. Figure 5.1a shows a representative time series
of the three factors found for experiment 4. Factor 2 can be interpreted as early SOA product,
while factor 3 represents the later SOA product. Figure 5.1b includes the mass spectra input
(factor 1) and output from the ME-2 model runs.
5.5 Supplementary material 55
Figure S 5.1. a) Time series of the concentration of the three factors (factor 1: fixed blank B3 spectrum, factor 2+3: two free spectra) and b) corresponding normalized mass spectra.
56 5 The link between organic aerosol mass loading and degree of oxygenation
Figure S 5.2. Van Krevelen diagram (H : C vs. O : C ratio) of the nine experiments together with the observed range of ambient SOA represented by dashed lines (Ng et al., 2011a) and blank experiment B3. Data points represent 30 min averages, except for Expt. 4 (60-min average). Arrows indicate the time when mass spectra for ME-2 model runs were taken.
Figure S 5.3. Comparison of OH exposures derived from α-pinene decay and butanol-d9 decay for experiments where butanol-d9 was above detection limit throughout the entire experiment. The dashed line represents the 1:1 line.
5.5 Supplementary material 57
Retrieval of the OH exposure of experiment 1 and 2 from a repeat experiment
As the decay of α-pinene in the beginning of experiment 1 and 2 was very rapid, using the α-
pinene method including the extrapolation to the whole experiment time leads to a possibly
strong overestimation of the OH exposure. For this reason a repeat experiment was conducted
which showed the same characteristics in α-pinene decay, but with the OH tracer butanol-d9
present for the whole experiment time (See Figure S 5.4). The repeat experiment resembles
strongly experiment 2, which has the same initial α-pinene concentration (14 ppbv). During
experiment 1 (with an initial α-pinene concentration of 7 ppbv), the reactant decays within the
same time. This lower initial α-pinene concentration is also the reason for the lower O3
production. The replaced OH exposures derived from the α-pinene decay for experiments 1
(black line) and 2 (turquoise line) are shown in the lower panel together with the OH exposure
of the repeat experiment (purple line).
Figure S 5.4. The α-pinene and O3 concentrations of experiment 1, 2 and the repeat experiment are shown as a function of light exposure time (upper panel). The lower panel shows the OH concentration and exposure retrieved from the decay of the tracer butanol-d9, present during the repeat experiment as well as the OH exposures derived from the α-pinene method, which were replaced by the repeat experiment for analysis.
58 5 The link between organic aerosol mass loading and degree of oxygenation
Figure S 5.5. OH exposures for the nine different experiments (color code) derived from the decay of α-pinene, butanol-d9 or a combination of both. The OH exposure of experiment 1 and 2 was derived from a repeat experiment.
Figure S 5.6. The measured organic mass concentration (green) was fitted exponentially (black) for the last three hours of experiment 5 where wall loss dominates over organic mass production. This procedure results in a lower limit of the wall loss corrected organic mass concentration (purple).
5.5 Supplementary material 59
Figure S 5.7. Thirty-minute averages (except expt. 4: 60-min) of O : C ratio vs. organic mass fraction f44 (a) and of hydrogen-to-carbon ratio vs. organic mass fraction f43 (b) color coded for the nine different experiments; 2-min data is represented by the grey dots. The linear regressions are compared to the fit of Aiken et al. (2008) and to the linear and polynomial fit in Ng et al. (2011a).
60 5 The link between organic aerosol mass loading and degree of oxygenation
Figure S 5.8. O : C ratio as a function of OH exposure for the nine smog chamber experiments. The data was fitted with a line for the period when aging dominates, i.e. after the peak of suspended organic mass is reached. The slopes of ∆O : C/∆(OH exposure) are shown in Table S 5.4. An OH exposure between 3 and 25 × 107 cm-3 h is required to increase O : C by 0.05.
Figure S 5.9. Squares of the Pearson correlation coefficients, R², of measured mass spectra in comparison with LV-OOA (filled symbols) and SV-OOA (empty symbols) reference spectra (Ng et al., 2011b) as a function of the organic mass concentration (wlc). The correlation was performed on 30-min averaged MS at specific OH exposures ( ± 15 min) indicated by the color code. The corresponding mass spectra are presented in Figure S 5.10.
5.5 Supplementary material 61
62 5 The link between organic aerosol mass loading and degree of oxygenation
5.5 Supplementary material 63
64 5 The link between organic aerosol mass loading and degree of oxygenation
5.5 Supplementary material 65
Figure S 5.10. Thirty-minute-averaged organic mass spectra of the nine experiments at OH exposures (if reached) of 2·, 4·, 6·, 8·, and 11 × 107 cm-3 h ( ± 15 min), together with reference LV-OOA and SV-OOA spectra from Ng et al. (2011b). The reference spectra were converted to the fragmentation table of Aiken et al. (2008) and normalized. Correlation tests of each spectrum with both reference spectra were performed, while m/z's directly proportional to m/z 44 and m/z's present in only one, the measured or reference spectrum, were excluded.
___________________________________________________________________________
6 Higher relative humidity and VOC/NOx
increase α-pinene secondary organic aerosol
yields
___________________________________________________________________________
L. Pfaffenberger1, I. El-Haddad1, J. Dommen1, C. Marcolli2, P. Barmet1,+, C. Frege1, S.
M. Platt1, E. A. Bruns1, M. Krapf1, J. G. Slowik1, R. Wolf1, A. S. H. Prévôt1 and U.
Baltensperger1
1 Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen, Switzerland
2 Institute for Atmospheric and Climate Science, ETH Zurich, 8092 Zurich, Switzerland
+ Now at: (Department Construction, Traffic and Environment, Canton of Aargau, 5001 Aarau, Switzerland)
in preparation for Atmospheric Chemistry and Physics
68 6 The link between organic aerosol mass loading and degree of oxygenation
Abstract
Secondary organic aerosol (SOA) yields from the photooxidation of the volatile organic
compound (VOC) α-pinene were investigated in smog chamber (SC) experiments at low
(~25 %) and high (~60 %) relative humidity (RH), various NOx/VOC ratios (0.04–3.8) and
with different seed chemical compositions (sulfate-containing or hydrophobic organic). A
combination of scanning mobility particle sizer and Aerodyne high resolution time-of-flight
aerosol mass spectrometer data was used to determine SOA mass concentration and chemical
composition. High RH increased yields (SOA formed-to-precursor reacted) up to six times
(1.5–6.4) compared to low RH, with greater increases for the most hygroscopic/acidic seeds.
The yields at low NOx/VOC (< 0.1) ratios were in general higher compared to yields at high
NOx/VOC (1.2–3.8) ratios. This NOx dependence follows the same trend as seen in previous
studies for α-pinene SOA.
Using Van Krevelen diagrams (plotting H : C vs. O : C), we show that the NOx/VOC ratio has
a strong effect on the aerosol chemical signature. For the same equivalent OH (hydroxyl
radical) exposure, experiments at low NOx/VOC ratios formed products with higher H : C
while experiments with higher NOx/VOC ratios showed lower H : C. This is expected from
higher formation yields of hydroxyl functional groups and peroxides at low NOx, compared to
organonitrates and carbonyls at high NOx.
While previous studies suggest a major effect of the relative humidity on particle chemical
composition via e. g. oligomerisation, we conclude, based on size-resolved data in this study,
that most of the α-pinene reaction products are not absorbed by the chosen inorganic and
organic seeds, rather, the seeds provide a surface for condensation. Our results are consistent
with literature observation indicating that there is no inorganic-organic mixing at different
RH. This study clearly presents varying yields dependent on the experimental conditions, for
the same α-pinene concentration reacted. We present wall-loss-corrected yields as a function
of the absorptive mass concentration consisting of organics and the associated liquid water
contents. We parameterized the volatility distributions for the use in modelling studies. It
might occur in the ambient atmosphere, that SOA loadings are sensitive to slight changes in
the absorptive mass concentration. To accurately predict SOA yields, the NOx/VOC ratio and
relative humidity have to be considered in models.
6.1 Introduction 69
6.1 Introduction
Organic aerosol (OA) accounts for 20 to 90 % of the submicron ambient aerosol (Jimenez et
al., 2009 and references therein), a great part of which is secondary organic aerosol (SOA)
formed via the condensation of low volatile oxidation products of gas-phase precursors.
Several direct (e.g. radiocarbon dating) and indirect observations underline the key role of
biogenic volatile organic compounds (VOC) in SOA formation (El Haddad et al., 2013 and
references therein). Current state-of-the-art models are unable to predict the burden of
biogenic SOA, especially in urban atmospheres (Hoyle et al., 2011), highlighting a
fundamental deficit in our knowledge of the chemical pathways and phase partitioning
mechanisms by which SOA accumulates and evolves in the atmosphere.
The ensemble of gaseous and particulate phase species involved in SOA formation is
immensely complex. The compounds relevant for SOA formation are often a minor gas phase
fraction, resulting in yields (SOA formed-to-precursor reacted) of only a few percent. Their
chemical composition and volatility distribution strongly depend on the oxidation conditions,
most notably on the fate of organic peroxy radicals (RO2), which either react with nitrogen
oxides (NOx) or other peroxy radicals (RO2 and HO2). The influence of NOx on the oxidation
mechanisms and SOA formation is commonly described by the NOx/VOC cycle and has been
under close scrutiny lately. For most light precursors, such as isoprene and monoterpenes
(including α-pinene), SOA yields appear to be strongly influenced by the NOx/VOC ratio,
with a general enhancement observed under low NOx conditions (Ng et al., 2007; Presto et al.,
2005). Another factor influencing SOA yields is the dynamic nature of the semi-volatile
species involved in SOA formation. These are subject to ongoing chemical degradation,
which may lead to compounds of either lower or greater volatility (Kroll and Seinfeld, 2008).
As a consequence, SOA yields and degrees of oxygenation (described by the atomic oxygen
to carbon ratio O : C) may not be constant, depending on the extent to which these species
were exposed to oxidants.
SOA yields are generally described by the absorptive equilibrium partitioning of condensable
species to a well-mixed liquid phase (Odum et al., 1996), which depends upon the chemical
species’ saturation vapour pressures (classically two model products are considered) and their
liquid-phase activities (modified Raoult’s law). Donahue and co-workers have proposed the
use of a “volatility basis set” (VBS) for a better representation of the wide range of OA in the
atmosphere and the ongoing oxidation of semi-volatile organics (Donahue et al., 2011; 2012
and references therein). However, several difficulties remain in estimating or measuring the
70 6 The link between organic aerosol mass loading and degree of oxygenation
saturation vapor pressures, molar activity coefficients and the mean molecular weight of the
condensing species (e.g. Clegg et al., 2008b, a).
Difficulties increase when considering the role of relative humidity (RH) and of inorganic
particles on organic partitioning (Zuend and Seinfeld, 2013 and references therein). In
addition to its potential influence on the kinetics of gas-phase reactions (e.g. the increased
formation rate of hydroxyl radicals (OH) with increasing H2O), from a thermodynamics point
of view, water interacts with SOA components by altering the water content of aerosol
particles (also at sub saturation conditions) and hence the equilibrium concentration of water
soluble organic compounds. An increase in aerosol-phase organics can be achieved by 1)
increasing the absorptive particulate mass, by 2) decreasing the average molecular weight of
condensed species or by 3) decreasing the activity coefficients of organic species (Pankow,
1994). Therefore, it is expected that an increase in particulate water content would in principle
enhance SOA yields of water-miscible species. Model calculations predict a pronounced
effect at low organic mass loadings (Pankow, 2010). An RH dependent yield has been
experimentally reported for a number of precursors including limonene, α-pinene and ∆3-
carene (Jonsson et al., 2006). Jonsson et al. (2006 and references therein) include previous
results from ozonolysis of the three aforementioned precursors. A substantial effect of RH on
SOA yields was observed only for studies at precursor concentration <1000 ppb (effect seen
with 124 ppb) and with large variation in RH (0.01 % & 31 % RH (Bonn et al., 2002); < 2–
58 % RH (Cocker et al., 2001); < 2–85 % RH (Jonsson et al., 2006)).
This RH effect is potentially enhanced by an acid catalysed reactive uptake of SOA products
onto the wet surface of particles (Kroll and Seinfeld, 2008; Kleindienst et al., 2006; Jang et
al., 2002; Iinuma et al., 2007). While this has been shown to play a key role for particular
oxygenated VOCs, e.g. glyoxal (Clegg and Seinfeld, 2006), SOA from a number of
precursors was found to be marginally affected by aqueous phase reactions (e.g. Ng et al.,
2007). However, the impact of RH on organic partitioning can be severely suppressed by
considerable deviations from ideal mixing between the condensing organic species and the
prevailing condensed phase. A growing number of studies shows that internally mixed
organic/ inorganic/ water aerosol particles may undergo a salting out effect, developing two
stable liquid phases: an aqueous electrolyte solution and an organic solution. The miscibility
of an organic analyte in an aqueous solution of electrolytes depends on numerous factors
including temperature, relative humidity, organic compound polarity commonly predicted by
its O : C, species relative contributions in bulk particulate matter and the chemical nature of
the electrolytes (Zuend and Seinfeld, 2013; You et al., 2013). For example, phase separation
6.2 Methods 71
was observed to always occur for organic compounds with an O : C < 0.5 and at low relative
humidity (You et al., 2013), and is especially pronounced in the case of ammonium sulfate
(compared to ammonium hydrogen sulfate and nitrate). Neglecting phase separation of
organic compounds and the effect of RH thereon bears the potential for invalid yield
predictions.
In this study, we investigate through systematic smog chamber experiments SOA formation
from the oxidation of α-pinene, a major biogenic precursor. The aim of this study is to
examine the impact of NOx/VOC ratios and particulate water content on SOA chemical
composition and yields. This is performed by varying relative humidity, NOx/α-pinene ratios
and aerosol seed composition (hygroscopicity, acidity). SOA yields and volatility
distributions reported here may aid the parameterization of the NOx and particulate water
dependence of α-pinene SOA for the use in atmospheric models.
6.2 Methods
6.2.1 Experimental setup and instrumentation
20 experiments (see Table 6.1) were carried out in the Paul Scherrer Institute (PSI) smog
chamber (SC): a 27 m³ Teflon bag suspended in a temperature-controlled wooden housing
(Paulsen et al., 2005). Photochemistry was initiated by four xenon arc lamps (4 kW rated
power, 1.55×105 lumens each, XBO 4000 W/HS, OSRAM), facing parallel to the SC bag,
emitting a light spectrum similar to the solar spectrum, and 80 black lights (Philips, Cleo
performance 100 W) to accelerate the aging process, located underneath the SC bag, with
emission between 300–400 nm wavelength (light characterisation in Platt et al. (2013)). A
reflecting aluminum foil surrounds the SC bag to maintain light intensity and light diffusion.
Various parameters were monitored in the SC. The temperature (T) and RH measurement was
optimized by passing SC air through a radiation shielded sensor. One of two different high
resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS, Aerodyne Research, Inc.,
Billerica, MA, USA) was operated during three different campaigns to measure online size-
resolved chemical composition (organics, ammonium, nitrate, sulfate, chloride) of non-
refractory particles (DeCarlo et al., 2006). The HR-ToF-AMS were equipped with two
different PM2.5 lenses (Williams et al., 2013) to sample particles up to large diameters above
1 µm. The sampled aerosol was dried (~10 % RH) before entering the HR-ToF-AMS. A
72 6 The link between organic aerosol mass loading and degree of oxygenation
supporting flow of ~1.5 L min-1 was maintained parallel to the HR-ToF-AMS to minimize
diffusive losses in the sampling lines. The HR-ToF-AMS data was corrected for gas-phase
contributions.
Two scanning mobility particle sizers (SMPS) were additionally deployed for the
measurement of the aerosol size distributions. The first SMPS (condensation particle counter,
CPC 3022 (TSI), and custom built differential mobility analyser, DMA: extended length Leff =
0.93 cm, dm max=1000 nm, recirculating sheath flow) was connected to the HR-ToF-AMS
sampling line to analyze the dried particles. A second SMPS (SMPSwet, TSI: CPC 3022A,
DMA classifier 3081, recirculating sheath flow) and a CPC (TSI: CPC 3025A) measured the
wet particle number size distribution and total number concentration (d > 3 nm), respectively.
Gas-phase compounds with a higher proton affinity than water (166.5 kcal mol-1) were
measured with a proton transfer reaction mass spectrometer (PTR-MS, Ionicon). The PTR-
MS was calibrated before each experiment for α-pinene detected at m/z 137 and m/z 81; the
accuracy of these measurements was estimated to be ~5 %, based on the purity indicated on
the calibration gas cylinder.
A chemiluminescence-based NOx instrument (Monitor Labs 9841A NOx analyzer) was
attached to the HONO source to monitor the injected concentration throughout the
experiment. A modified NOx instrument including a blue-light photolytic NO2-to-NO
converter (Thermo Environmental Instruments 42C trace level NOx analyzer) and two ozone
monitors (Monitor Labs 8810 ozone analyzer, Environics S300 ozone analyzer) monitored
NOx and O3 in the SC.
6.2.2 Smog chamber operation and aerosol seeding
SOA formation and growth from the precursor α-pinene was induced by the following SC
operation sequence: (1) humidification of the chamber, (2) addition of seed aerosol, (3)
introduction of VOCs, (4) addition of nitrous acid (HONO), (5) addition of nitrogen oxides
(equal amounts of NO + NO2) if applicable, (6) an equilibration period (30–45 min), (7)
switching on of xenon and black lights to generate OH radicals, and (8) a reaction time of 5 to
20 h (corresponding to 0–2 × 108 cm-3 h OH exposure, see Sect. 6.2.4). Experimental
conditions for each individual experiment are summarized in Table 6.1. Before each
experiment, the SC was cleaned by the injection of several ppmv of ozone for 5 h and
irradiation with black lights for 10 h at 20 °C, followed by a flushing period with pure air and
6.2 Methods 73
high relative humidity (~60 %) at ~30 °C for at least 20 h. To ensure that organic matter (OM)
formed during the experiments is not significantly influenced by background contamination in
the SC, three blank experiments were carried out (high RH, seed aerosol, lights switched on,
but without addition of α-pinene). The organic mass concentration formed was substantially
lower (< 0.1 up to 2.8 µg m-3) than during comparable experiments (similar NOx/VOC and
RH).
In the chamber, the temperature varied within a range of 21 °C to 26 °C between experiments.
Due to heat from the xenon and black lights, the temperature increased, stabilizing only ~1 h
after experiment start. The increase in temperature of 1–4 °C led to an absolute decrease in
RH of ~2-20 %, thus the range given in Table 1, 23–75 % RH, is representative for the
temperature-stable period afterwards. Liquid-phase α-pinene (98 %, Aldrich) and an OH
tracer (9-times deuterated butanol, 98 %, D9, Cambridge Isotope Laboratories), hereafter
referred to as butanol-d9 (1 µL injected ≈ 10 ppb in the SC), were sequentially injected into
an evaporation glass bulb heated to 80 °C. The two VOCs were carried into the bag by a
dilution and flush flow (each 15 L min-1, maintained for 15 min) from an air purifier (737-250
series, AADCO Instruments, Inc., USA), further referred to as “pure air”. Initial α-pinene
concentrations were 16.1–31.7 ppbv.
HONO was used as a source of both NO and OH, produced in a reaction vessel by continuous
mixing of the reagents sodium nitrite (NaNO2, 1 mmol L-1 in milli-Q H2O) and three different
concentrations of sulfuric acid solutions (H2SO4, 1 mmol L-1 (expt. 1-6), 10 mmol L-1 (expt. 7,
8, 11, 13) and 100 mmol L-1 (expt. 9, 10, 12, 14) in milli-Q H2O) (Taira and Kanda, 1990).
The HONO product was carried by 2.5 ± 0.2 L min-1 pure air flow into the SC and particulate
H2SO4 was minimised by a Teflon filter applied between HONO source and SC. 2 ppbv
(± 10 %) of HONO were injected before lights on to initiate photochemistry and the injection
was continued throughout all experiments. In addition, equal concentrations of NO (99.8 %;
1005 ppmv ± 2 %) and NO2 (purity: 98 %; 1005 ppmv ± 3 %), resulting in 19.6–75.1 ppbv
initial NOx, were added during experiments with NOx/α-pinene > 1. Within the results section,
the two terms “low NOx” and “high NOx” refer to the following conditions:
- low NOx = NOx/α-pinene < 0.1: HONO injected continuously (indicated by the
asterisks (*) in Table 6.1 and figures).
- high NOx = NOx/α-pinene > 1: Initial injection of NO + NO2 with continuous HONO
injection
74 6 The link between organic aerosol mass loading and degree of oxygenation
For high NOx experiments the initial NOx concentration, which decays with time to lower
values, and for low NOx experiments the mean NOx concentration is given in Table 6.1.
During 14 experiments (no. 1–14) and two blank experiments, a solution (1 g L-1) of
ammonium hydrogen sulfate (NH4HSO4, Aldrich) in ultrapure milli-Q water was nebulized
(0.6 L min−1) and introduced into the SC with a pure air dilution flow of 10 L min−1 to act as
seed particles. To keep the seed aerosol as far as possible in a liquid state, no drier was used
behind the nebulizer. We determine the acidity of the seed particles, here defined by the
NH4/SO4 ratio measured by the HR-ToF-AMS. A NH4/SO4 ratio between 1 and 2 indicates a
neutral seed composition, a mixture of NH4HSO4, (NH4)3(SO4)2 (letovicite) and (NH4)2SO4.
For simplicity, we replaced (NH4)3(SO4)2 by an equal mix of NH4HSO4 and (NH4)2SO4 for the
assumption of density and growth factors. By contrast, a NH4/SO4 ≤ 1 indicates an acidic
seed, including a mixture of NH4HSO4 and H2SO4.
During experiments 7–14, the nebulized NH4HSO4 solution was partly neutralized to
(NH4)2SO4 presumably by background NH3 released from the walls, as indicated by the molar
NH4/SO4 ratio (Figure S 6.3, Supplement). During experiments 1–6 the seed was composed of
a mixture of NH4HSO4 and H2SO4, due to a significant addition of gas-phase concentration of
H2SO4 via the HONO injection, suppressing the seed neutralization by NH3.
Additionally, three α-pinene experiments (no. 15–17) and one blank experiment were
conducted using an inert hydrophobic fluorinated hydrocarbon as seed (further referred to as
CF-seed; CF3CF2CF2O-[CF(CF3)CF2-O-]nCF2CF3; Krytox® 1525). These experiments were
conducted to isolate the humidity effect on α-pinene SOA from possible water-phase reactions
happening during the hydrophilic seed experiments in an inorganic-seed-SOA-mixture. The
CF-seed was generated via evaporation of the fluorinated hydrocarbon in the liquid phase at a
temperature of 125–145 °C and subsequent homogeneous nucleation in a pure air flow of
2.4 ± 0.1 L min-1. The CF-seed concentration was 6.7–10.0 µg m-3 when lights were switched
on, and decayed to values below detection limit of the HR-ToF-AMS (0.1 µg m-3), after α-
pinene SOA condensation. The CF-seed mass spectrum in the HR-ToF-AMS is clearly
distinct from α-pinene SOA, with main contributions at m/z 69 (CF3), m/z 169 (C3F7) and
m/z 119 (C2F5) (Figure S 6.4 and Table S 6.1, Supplement). Table 6.1 lists the seed
composition and estimated physical state of each experiment dependent on RH (acidic =
ammonium hydrogen sulfate (NH4HSO4) & sulfuric acid (H2SO4); neutral = ammonium
sulfate ((NH4)2SO4) & ammonium hydrogen sulfate (NH4HSO4); CF = fluorinated carbon).
6.2 Methods 75
There is no measurable efflorescence for NH4HSO4; efflorescence of (NH4)2SO4 happens at
35 % RH (Martin, 2000).
6.2.3 Estimation of the hygroscopic growth factors and liquid water content
The absolute liquid water content (LWC) of the aerosol particles was derived for the bulk
aerosol mass and the size resolved mass distribution based on literature growth factors, the
measured RH and chemical composition. The growth factor GF (RH) of a particle is defined
as the ratio of wet diameter at a given RH to the dry diameter: ⁄ .
Inorganic GFs were taken from the Aerosol Diameter Dependent Equilibrium Model
(ADDEM, Topping et al., 2005) for diameters of 360 nm. GFs of organics were derived using
the relationship between the hygroscopicity parameter κ and the degree of oxygenation
[κ = 0.29×(O : C)] from Chang et al. (2010), well representing the hygroscopicity of α-pinene
SOA measured by Massoli et al. (2010). The measured degree of oxygenation at an OH
exposure of (2.0 ± 0.5) ×107 cm-3 h was used to derive κ, which in turn was converted to GF,
assuming a negligible curvature (Kelvin) effect (Kreidenweis et al., 2005):
1 κ %
%
(6.1)
The mixed GFs for aerosol containing inorganic and organic species were determined using
as a first approximation the Zdanovskii-Stokes-Robinson (ZSR) volume mixing rule (Stokes
and Robinson, 1966):
∑ ∙ (6.2)
Where εi and GFi(RH) denote the volume fraction and GF (RH) of species i, respectively. The
H2O volume ( was calculated using the definition of GF (RH) and the dry volume (Vdry):
∙ 1 (6.3)
multiplied by the density of water (1 g cm-3) results in the LWC.
The dry (Sdry) and wet (Swet) surfaces were calculated with Eq. (6.4) and Eq. (6.5),
respectively:
6 ∙ / (6.4)
6 ∙ / (6.5)
76 6 The link between organic aerosol mass loading and degree of oxygenation
The LWC and surface distributions were derived using size resolved pToF (particle time-of-
flight) data. Due to the low pToF signal of NH4, its surface distribution was estimated based
on SO4 pToF measurements.
6.2.4 Determination of OH exposure and extent of α-pinene ozonolysis
The gas-phase composition, the resulting OH concentration and thus the photochemical age of
a reaction system may considerably vary between experiments. Furthermore, within a single
experiment the photochemical age is not necessarily directly proportional to the light
exposure time. Therefore, we here discuss reaction time in terms of OH exposure (cm-3 h),
defined as the OH concentration integrated over time. OH exposures were derived based on
the decay of the OH tracer butanol-d9, detected by the PTR-MS as M+H+-H2O at m/z 66,
following the methodology introduced by Barmet et al. (2012):
OHexposure,
∙ ∆
∆dt (6.6)
Where butanol-d9 and kOH, butanol-d9 (= 3.4 × 10-12 cm3 molecules-1 s-1) are the butanol-d9
concentration and its reaction rate with OH, respectively. t is the time after lights on, V the SC
volume (we assume as a first approximation a constant chamber volume), and fdil the dilution
flow due to HONO input (Sect. 6.2.2).
The percentage of α-pinene reacted with OH was derived based on Eq. (6.7):
, ∙ , ∙ (6.7)
Where [α-pin], [O3] and [OH] denote the concentrations of α-pinene, O3 and OH, and kOH, α-pin
(= 5.3 × 10-11 cm3 molecules-1 s-1) and kO3, α-pin (= 8.9 × 10-17 cm3 molecules-1 s-1) the reaction
constants of α-pinene with OH and O3, respectively. The production of O3 was faster under
high NOx compared to low NOx, due to a more efficient VOC-NOx catalytic cycle. Therefore,
the lowest percentage (~65 %) of α-pinene reacted with OH was achieved during experiment
no. 9, under high NOx, while for all other experiments 67.9–87.8 % of α-pinene reacted with
OH (Table 6.1). We also expect that the further processing of the first generation products
formed via α-pinene reaction with OH or O3 – that don’t contain C=C bonds – to
6.2 Methods 77
predominantly proceed through reactions with OH. Accordingly, we conclude that SOA
compounds detected under these conditions are mainly from OH chemistry.
Table 6.1. Overview of experimental conditions. Seed types {acidic = ammonium hydrogen sulfate (NH4HSO4) & sulfuric acid (H2SO4); neutral = ammonium sulfate ((NH4)2SO4) & ammonium hydrogen sulfate (NH4HSO4); CF = fluorinated carbon (see Sect.6.2.2)} and their estimated phase states {(L) = liquid; (-) = liquid and/or solid}. Initial seed mass concentrations; relative humidity (RH); measured mean (*) NOx concentrations during low NOx experiments and measured initial NOx concentrations during high NOx experiments; measured initial α-pinene concentrations (which reacted before an OH exposure of (2.0 ± 0.5) ×107 cm-3 h) and their estimated fractions reacted with OH radicals in %, rest reacted with O3). NOx/α-pinene ratios; wall-loss corrected organic mass concentrations and corresponding yields averaged over the OH exposure of (2 ± 0.5) ×107 cm-3 h. Standard deviations (1sd) given in brackets are measurement variability. Horizontal lines separate experiments with different i) seed composition, ii) RH, iii) NOx/α-pinene. Blank experiments (B1, B2 and B3) are listed at the very bottom.
No seed RH NOx α-pin α-pin NOx/ org (wlc) yield (wlc)
type (phase) initial initial or initial = decay α-pin at OH exp.:
mean(*) reacted by OH 2(±0.5) × 107 cm-3 h
µg m-3 % ppbv ppbv % µg m-3 %
1 acidic (L) 8.0(0.5) 69(2) 44.4(0.8) 20.7 80.0 2.1 13.4(0.2) 11.5
2 acidic (L) 12.3(0.5) 67(2) 70.4(1.3) 18.7 80.3 3.8 8.6(0.1) 8.1
3 acidic (L) 4.9(0.3) 66(2) 19.6(0.7) 16.1 81.6 1.2 12.6(0.6) 13.8
4 acidic (L) 4.7(0.2) 29(1) 23.6(0.6) 19.9 81.3 1.2 3.9(0.0) 3.5
5 acidic (L) 8.0(0.3) 28(1) 52.1(0.6) 20.3 74.6 2.6 2.1(0.1) 1.8
6 acidic (L) 5.2(0.3) 27(1) 1.3(0.4)* 18.3 87.8 0.071 12.0(0.5) 11.6
7 neutral (L) 8.8(0.4) 67(1) 0.7(0.2)* 20 81.9 0.037 16.2(0.4) 14.3
8 neutral (L) 4.3(0.6) 60(1) 1.0(0.2)* 18.7 86.5 0.052 12.3(0.4) 11.6
9 neutral (L) 5.5(0.2) 56(2) 65.8(0.8) 30.9 65.0 2.1 11.1(0.1) 6.4
10 neutral (L) 4.4(0.2) 50(1) 1.3(0.2)* 30.6 79.2 0.041 29.6(1.1) 17.1
11 neutral (-) 4.1(0.2) 26(1) 0.7(0.3)* 18.9 81.3 0.039 5.5(0.2) 5.1
12 neutral (-) 3.6(0.1) 26(1) 1.9(0.4)* 30.5 78.4 0.062 20.3(1.3) 11.8
13 neutral (-) 8.2(0.3) 25(1) 1.1(0.3)* 19.6 87.4 0.055 5.3(0.1) 4.8
14 neutral (-) 3.2(0.2) 23(1) 75.1(0.7) 27.8 69.4 2.7 2.4(0.1) 1.5
15 CF (L) 7.1(0.3) 58(1) 56.2(0.7) 31.7 67.9 1.8 9.8(0.1) 5.4
16 CF (L) 10.0(0.5) 58(2) 58.3(0.5) 31.3 73.9 1.9 10.7(0.1) 6.1
17 CF (L) 6.7(0.1) 26(1) 53.3(0.6) 30.5 69.7 1.7 4.7(0.1) 2.1
B1 CF (L) 0.3(0.1) 58(2) 53.0(0.6) - - - < 0.1 -
B2 neutral (L) 4.5(0.7) 68(2) 0.9(0.5)* - - - 2.8(1.0) -
B3 acidic (L) 3.8(0.2) 75(3) 1.4(0.3)* - - - 0.5(0.1) -
78 6 The link between organic aerosol mass loading and degree of oxygenation
6.2.5 Determination of suspended and wall-loss-corrected organic mass and yield
Suspended OA mass. Determining accurate measures of the total organic aerosol
concentration, [OA], is crucial for obtaining accurate aerosol mass yields, Y. Nevertheless, we
note that our main objective is determining the effects of changes in the environmental
conditions (i.e. NOx concentration, RH and seed composition) on SOA yields. Therefore,
systematic biases in the yield determination, thoroughly discussed below, may marginally
influence our conclusions. The suspended organic mass concentration, was derived by
utilizing the chemical composition measurements from the HR-ToF-AMS scaled to the total
volume measured by the SMPS, using compound-specific densities (ρorg = 1.4 g/cm³, ρNH4HSO4
= 1.79 g/cm³, ρ(NH4)2SO4 = 1.77 g/cm³, ρH2SO4 = 1.83 g/cm³).
For some experiments (9, 10, 12 and 14-17), the organic mass concentrations determined by
the HR-ToF-AMS were corrected for a below unity transmission efficiency at the lower edge
cut-off of one of the two PM2.5 lenses employed (Figure S 6.1 and Figure S 6.2, Supplement).
Additionally, for organic mass calculation, we have considered that the measured NO3 signals
are entirely related to organonitrates, rather than NH4NO3. This assumption mainly stems
from (1) simultaneous increases of the NO3 signal in the same particle size region as OA (see
pToF-data, Sect. 6.3.3), while inorganic nitrate would be expected to mix within the
electrolyte rich aerosol at larger diameters and (2) the occurrence of NO3 under acidic
conditions, thermodynamically unfavorable for NH4NO3. This is also supported by the higher
NO+/NO2+ ratios measured in the SC compared to ratios recorded during NH4NO3
nebulization (on average 1–2.8 times higher, Supplement Figure S 6.10), typically expected
from organonitrates (Farmer et al., 2010). We cannot exclude the presence of NH4NO3, which
would increase the calculated LWC by only 1–13 % and decrease the calculated OA mass by
only 2–7 %, assuming all detected nitrate to be NH4NO3. Finally, for the yield calculations,
we consider that the accuracy of the aerosol phase measurements to be around 30 %.
Wall-loss-corrected-OA mass. To correct the total OA concentration for losses of particles
and vapours to the chamber walls, we use Eq. (6.8), introduced by Hildebrandt et al. (2011),
based on the mass balances of the suspended organic aerosol mass, , and the mass of the
organic aerosols on the walls, (summed up to derive [OA]):
ω ∙ ∙ (6.8)
Here, represents the loss rate of organic particles to the walls, derived by fitting
between 5–8 h after lights were switched on, when SOA production is expected to be
6.2 Methods 79
negligible (α-pinene concentration < 1 ppbv, Figure S 6.6 and Table S 5.2, Supplement). We
determine an average loss rate of 0.13 h-1, corresponding to a particle half-life of 5.3 h. This is
consistent with theoretical values calculated for the loss of 100-300 nm particles by
diffusional deposition and gravitational settling under our conditions. This average was
used in the case of insufficient data point statistics to perform accurate fitting. In Eq. (6.8), ω
is a dimensionless proportionality coefficient between the mass of organic vapors that
partition into the wall-deposited particles and the mass of organic vapors that partition into the
suspended particles, with ω ranging between 0 and 1. Here, for the base case calculations, we
neglect the condensation of organic vapors onto the wall-deposited particles (i.e. ω 0),
consistent with previous studies of α-pinene SOA production (Hildebrandt et al., 2011 and
references therein). This assumption gives a lowest estimate of SOA yields. Considering the
second limiting case: ω 1, which characterizes an equal partitioning of organic vapors
between the wall-deposited and suspended particles, would increase the determined [OA] and
Y.
We note that Eq. (6.8) does not take the loss of vapors onto the Teflon walls of the chamber
into consideration, which was recently reported to depend on the wall-to-seed surface ratio
and to greatly suppress SOA yields from laboratory chambers under certain conditions (Zhang
et al., 2014). We are convinced that gas-wall partitioning does not significantly influence the
interpretation of our results, focused on relative differences in the yields determined under
different conditions. This is because: (1) this effect was found to be minor for the α-pinene
SOA system (2) SOA mass formation rapidly evolved after lights were switched on and (3)
we have maintained a relatively constant wall-to-seed surface ratio for all experiments, crucial
for vapor-wall-losses; hence losses of organic vapors may lead to a systematic negative bias
in the determined yields, but do not influence the comparison between the experiments.
SOA yield determination and parameterization. SOA mass yields, Y, are defined in Eq. (6.9)
as the organic mass concentration formed, [OA], per precursor mass consumed, ΔCα-pinene:
(6.9)
For comparison purposes, Y are reported in Figure 6.2 and (Table 6.1) at an OH exposure of
(2.0 ± 0.5) ×107 cm-3 h, reached during all experiments. The parameterization of SC SOA
yields measured is based on the absorptive partitioning theory of Pankow (Eq. (6.10),
(Pankow, 1994)), which expresses the production of a set of semi-volatile surrogate products
(total number N) as a function of the mass yield of these products, αi, and their partitioning
80 6 The link between organic aerosol mass loading and degree of oxygenation
coefficients, ξi (a dimensionless quantity reflecting the condensed-phase mass fraction of
these products). The critical parameters driving the partitioning of these products are their
effective saturation concentration, Ci*, and the total concentration of the absorptive organic
phase, COA. As discussed below, we consider the absorptive organic mass as the sum of the
total OA concentration including organonitrates, [OA], and the liquid water content in this
phase (Sect. 6.3.3).
∑ ∑ 1∗
(6.10)
In Eq. (6.10), Ci* is a semi-empirical property (inverse of the Pankow-partitioning coefficient,
KP) reflecting the vapor pressure of the pure constituents, ,° , and their interaction with the
organic mixture (effectively including liquid phase activities, γi), as expressed in Eq. (6.11):
∗ ,°
(6.11)
Where Mi denotes the molecular weight of compound i, R the ideal gas constant and T the
temperature. Here, SC yields from single experiments are fitted as a function of COA using the
volatility basis set (VBS) (Donahue et al., 2006), which separates semi-volatile organics into
logarithmically spaced bins of effective saturation concentrations Ci*. In practice, a total
number of 4 bins spanning our measurement range were assumed: N = 4, Ci* = 0.1, 1, 10 and
100. To solve Eq. (6.10) for the parameters αi, we have introduced a novel approach using a
Monte Carlo simulation. This approach provides the best estimate of αi values representing
the measured yields, Y, from single experiments vs. the measured absorptive masses, COA. It
also offers a measure for the uncertainties related to the determination of the volatility
distributions (αi parameters) from SC experiments. The method proceeds as follows:
(1) A possible yield domain is inscribed against COA, based on our best estimates of the
measurement accuracy of SOA and α-pinene mass;
(2) A range of possible inputs is defined for the parameters αi;
(3) αi parameters are randomly generated over the range;
(4) Deterministic computations of Y vs. COA are performed using Eq. (6.10) and the generated
αi inputs.
(5) Yield curves that fall within the domain defined in step (1) are saved, aggregated and
presented as probability distribution functions (PDF).
6.3 Results 81
6.3 Results
6.3.1 SOA yield dependence on RH, NOx/α-pinene and aerosol seed composition
Figure 6.1 shows the suspended and wall-loss-corrected organic mass concentrations as a
function of OH exposure for experiments listed in Table 6.1. Two panels separate
experiments with ~20 ppbv (top panel) and ~30 ppbv (bottom panel) initial α-pinene
concentration. Asterisks indicate low NOx experiments and the same symbol shapes are used
for the same seed compositions. SOA mass is rapidly formed after lights were switched on
and the wall-loss-corrected mass reaches a certain plateau. This happens in general later for
experiments with higher SOA formed than for less SOA formed, at an approximate OH
exposure of 2 ×107 cm-3 h.
Figure 6.1. 20-min-averaged wall-loss-corrected (symbols & lines) and suspended (lines) organic mass concentrations as a function of OH exposure. Data is separated according to similar initial α-pinene concentration (20ppbv - top panel, 30ppbv - bottom panel). Seed composition is given in the legend and asterisks indicate low NOx experiments.
82 6 The link between organic aerosol mass loading and degree of oxygenation
In Figure 6.2, we examine the relationship between the yields at the same OH exposure of
(2.0 ± 0.5) ×107 cm-3 h and the prevailing experimental conditions: RH, NOx/α-pinene and
seed composition. Lines connect experiments with all parameters approximately constant
except RH (dashed) or NOx/α-pinene (solid). The NOx/VOC of experiment 5 lies between
expts. 1 and 2, the reason for the line split. We observe a clear influence of the RH on the
yields, increasing on average by 0.15 ± 0.06 % per 1 % RH, for the range investigated.
Despite the limited statistics, the extent of the RH effect was found to be highly dependent on
the seed chemical nature, with a greater influence for the acidic seed (0.22 ± 0.03 % per 1 %
RH, p < 0.001), the most hygroscopic aerosol, compared to the non-acidic seed
(0.15 ± 0.03 % per 1 % RH, p < 0.001) and the hydrophobic seed (0.09 ± 0.04 % per 1 % RH,
p = 0.05).
Figure 6.2. Average wall-loss-corrected yields at (2.0 ± 0.5) ×107 cm-3 h OH exposure as a function of RH. Symbol sizes represent α-pinene reacted, symbol colors represent NOx/α-pinene and symbol shapes represent seed composition according to Table 6.1. Experiments with similar NOx/α-pinene, seed composition and α-pinene reacted are connected with dashed lines showing the increase in yield for increased RH Experiments with similar RH, α-pinene reacted and seed composition are connected with solid lines showing the increased yield with decreasing NOx/α-pinene ratio.
6.3 Results 83
This indicates that the particulate water content plays a central role in the partitioning of SOA
compounds, either by altering the thermodynamic properties of the bulk phase (e.g. increasing
the absorptive mass or decreasing the compounds activity coefficients, non-reactive uptake)
or by providing a reactive sink for SOA semi-volatile species (e.g. formation of lower
volatility compounds/oligomers in the bulk phase, reactive uptake). These two processes will
be investigated below.
SOA yields are also significantly enhanced under low NOx conditions, in agreement with
literature data (Ng et al., 2007). The decrease in SOA yields against NOx/α-pinene ratio is
estimated at 3.3 ± 0.6 % (p < 0.001). Such decrease indicates that SOA compounds formed
under low NOx conditions are less volatile than those formed under high NOx conditions.
Overall, these results highlight the sensitivity of SOA yields to the prevailing oxidation
conditions and the particle bulk-phase composition. Therefore considering such conditions for
accurate predictions of the SOA burden in the atmosphere is needed.
6.3.2 SOA elemental composition
The effect of the experimental conditions on SOA chemical composition are investigated in
the Van Krevelen space in Figure 6.3a. The mean and standard deviation (1sd) of the
elemental O : C and H : C (atomic hydrogen to carbon ratio) at an OH exposure of
(2.0 ± 0.5) ×107 cm-3 h are shown by markers, while 1-h-averages for OH exposures >
2 ×106 cm-3 h are represented by solid lines. The overall region of H : C to O : C in the Van
Krevelen space is very comparable for all experimental conditions and to ambient data,
represented by the triangular shape (Ng et al., 2011a). Data of experiments 1-14, with
inorganic seed, follows a similar slope (-0.86, least orthogonal distance fit) with aging: An
increase in O : C during aerosol aging takes place under all conditions. Experiments 15-17
show lower H:C and O:C especially in the beginning due to some contribution of the
fluorinated hydrocarbon seed to these ratios. Experiments with very low organic mass loading
follow a similar slope as the other experiments, but with lower H : C and O : C.
84 6 The link between organic aerosol mass loading and degree of oxygenation
Figure 6.3. Van Krevelen diagrams: Mean (± 1 sd measurement variability) H : C versus O : C at OH exposure (2.0 ± 0.5) ×107 cm-3 h (symbols). Symbol colors indicate RH, symbol shapes the seed composition and the asterisk low NOx experiments. The triangular shape (solid black lines) represents the range of ambient SOA (Ng et al., 2011a). (a) Additionally included 1 h-averaged (lines) H : C versus O : C (for OH exposure > 2 × 106 cm-3 h) show similar region and trend for all conditions. The dashed line represents the (least orthogonal distance) fitted slope of expts. (1-14) with inorganic seed: -0.86. Expts. 15-17 show influence of CF seed compounds (data shown from suspended organic mass > 0.3 µg m-3). (b) Data separated by wall-loss-corrected organic mass concentrations to exclude concentration effects (left panel: 2-6 µg m-3; middle panel: 8-14 µg m-3; right panel: 16-30 µg m-3). The grey shaded areas include all low NOx experiments.
6.3 Results 85
In Figure 6.3b the data was separated according to the organic mass concentrations to isolate
the NOx and RH effects on the chemical composition from the possible influence of enhanced
partitioning of semi-volatile organic species to the aerosol phase due to a higher SOA loading
(Pfaffenberger et al., 2013). We observe that NOx levels have the highest influence on SOA
elemental composition. Generally, low NOx experiments (marked with asterisks) show a
higher H : C than high NOx experiments, indicated by the grey shaded areas at the upper end
of the figure.
This is even more pronounced at an early reaction stage (OH exposure < 2 × 106 cm-3 h, not
shown in Figure 6.3), where fresh SOA products formed during all low NOx experiments have
a higher H : C and lower O : C. Such influence of NOx levels on SOA elemental composition
is consistent with our general understanding of SOA chemistry: under low NOx, substantial
amounts of hydroperoxides would result in a higher H : C ratio than e.g. aldehydes/ketones
formed under high NOx conditions (Valorso et al., 2011). NOx levels also influence the
amount of organonitrate formed: considering that the entire nitrate signal arises from
organonitrates (i.e. a higher estimate of organonitrate contribution), we estimate molar ratios
of NO3 to carbon of ~1:30 for high NOx and ~1:100 for low NOx (Figure S 6.5, Supplement).
Assuming molecules with 10 carbon atoms, these ratios imply that every 3rd molecule
contains one NO3 functional group for high NOx vs. every 10th molecule contains one NO3
functional group for low NOx.
Conversely, we did not observe a significant effect of RH and seed acidity on SOA elemental
composition, despite of their significant influence on SOA yields. Furthermore, we could not
reveal any significant dependence between these parameters and the ratio of organic
fragments larger than m/z 150 to the total organic mass, a proxy for oligomers measured with
the HR-ToF-AMS (Figure S 6.8, Supplement).
6.3.3 Particle size dependent uptake of organic mass
As the seed composition and RH appear to greatly influence SOA yields, we examine in this
section the interaction between these parameters and SOA, through the investigation of the
aerosol size-resolved chemical composition. This information is used later to deduce the
behavior of the absorptive organic phase, while modeling the aerosol dynamics in the SC is
beyond the scope of this study.
a)
b)
Figure 6.4. Evolution of size distributions. Measured organic, SO4, NH4, NO3 mass distributions for OH exposures of 0×, (0.5 ± 0.2)×, (1.0 ± 0.3)× and (2.0 ± 0.5) ×107 cm-3 h. Black lines represent estimated liquid water content (method: Sect. 6.2.3; RH and individual GFs given in the legend, percentage in brackets: fractions of SO4). The calculated dry and wet surface distributions are shown as dashed lines on the right axes. (a) High NOx with more acidic seed: Experiments 3 and 4 with NOx/α-pinene = 1.2 and exp. 2 with NOx/α-pinene = 3.8. (b) Low NOx with less acidic seed: Experiments 8 and 13 with NOx/α-pinene ≈ 0.05. Additional figures in Supplement (Figure S 6.9).
88 6 The link between organic aerosol mass loading and degree of oxygenation
Figure 6.4 shows the aerosol size resolved chemical composition at 0 ×107 cm-3 h,
(0.5 ± 0.2) ×107 cm-3 h, (1.0 ± 0.3) ×107 cm-3 h and (2.0 ± 0.5) ×107 cm-3 h OH exposure for
five experimental conditions. The liquid water mass distributions (black lines) and the dry and
wet surface distributions (dashed lines) were estimated as described in Sect. 6.2.3. Figure 6.4a
includes high NOx experiments 3 and 4 (NOx/α-pinene = 1.2) and experiment 2 (NOx/α-
pinene = 3.8). Figure 6.4b includes low NOx experiments 8 and 13 (NOx/α-pinene
ratio ≈ 0.05). Additional figures for experiments 1, 5 and 6 are available in the Supplement
(Figure S 6.9).
For all experiments, the aerosol size distributions show two externally mixed aerosol
populations, with a mode at lower diameters (~200 nm, mode1) mostly containing SOA and a
second mode at larger diameters (~400 nm, mode2) mostly consisting of the seed. We note
that the particle size distribution evolved consistently under different conditions, with the
smallest seed particles growing with SOA condensation. For higher yields, the main SOA
mass occurs in mode1. For example, despite the sizeable increase of the yield with particulate
water content, we did not observe a significant enhancement of SOA in mode2 for acidic
conditions or with RH. In addition, we did not note any statistically significant correlation
between the initial seed volume and SOA yields (Table 1), but instead the aerosol uptake
seems to be driven by the wet particle surface (Figure 6.4). Such behavior would imply that
SOA semi-volatile compounds do not additionally partition or react in the electrolyte rich
phase, but rather the reactive or non-reactive uptake of these products onto the particle surface
is enhanced with the increase of the initial particulate water content. Homogeneous nucleation
events are excluded, as there is no rapid particle number concentration increase after lights
were switched on (Figure S 6.11, Supplement) and no mode evolving from very small to
larger diameters, seen from SMPS data.
We assume uptake of α-pinene products by the total organic mass (including organonitrates)
and derived the corresponding LWC as described in Sect. 6.2.3. Due to the strong dependence
of the SOA yield on the NOx/α-pinene ratio, the data presented in Figure 6.5 was separated
accordingly (upper panel: NOx/α-pinene < 0.1; lower panel: NOx/α-pinene > 1) and shown for
absorptive masses larger than 1 µg m-3. If the LWC was only contributing to the liquid
absorptive mass concentration, the yield curves for low and high RH experiments should
overlay. This is however only the case for experiments 10 and 12 at absorptive mass
concentrations > 6 µg m-3. For lower absorptive mass concentrations all experiments that are
comparable in their seed composition, NOx/α-pinene and α-pinene concentration reacted,
6.3 Results 89
show an enhancement in the yield for higher RH. This means that a process to
comprehensively describe the yield is missing, when only considering organics and H2O. We
suggest that this increase is due to the direct influence of gaseous and particulate water to the
partitioning coefficient which is increased when the average molecular weight is decreased by
adding H2O to the system. Models show that this effect is more pronounced for experiments
at low organic mass loading (Hallquist et al., 2009; Pankow, 2011 and references therein).
Another increase is observed with increasing seed acidity: Yields of expts. 1, 2 and 3 (acidic)
are higher than the yields of exp. 9 (neutral) and expts. 15 and 16 (CF-seed). This might be
related to enhanced acid-catalyzed heterogeneous reactions on the seed surface (Kroll and
Seinfeld, 2008) or to the higher hygroscopic growth factor for H2SO4 compared to (NH4)2SO4
and NH4HSO4 (Topping et al., 2005). Aqueous phase chemistry with a potential to form
highly oxidized organic acids or oligomers plays a minor role for enhanced yields found in
this study as no higher O : C in Van Krevelen diagrams (Figure 6.3) and no increased
oligomer fraction (Figure S 6.8, Supplement) is correlated with the increased yields.
Figure 6.5. 20-min-averaged measured (symbols) and fitted (lines) wall-loss-corrected SOA yield as a function of wall-loss-corrected absorptive mass concentration (organics + NO3 + H2O) for low NOx experiments (upper panel) and high NOx experiments (lower panel). Data was limited to 2 ×107 cm-3 h OH exposure. Symbol colors indicate RH, symbol shapes the seed composition.
90 6 The link between organic aerosol mass loading and degree of oxygenation
Data in Figure 6.5 was used to estimate the mass yields per volatility bin ai for each
experiment using Eq. (6.10). Figure 6.6 shows the probability density functions (PDF) of ai
values of 100 possible solutions for one low RH (No. 4) and the corresponding high RH (No.
3) experiment. The higher intensity of mass yields in the Ci* bins 10 and 100 for high RH
shows the increased partitioning of more volatile products during experiments with higher RH
and yield. More PDFs are provided in the Supplement, Figure S 6.12.
Figure 6.6. Probability density functions (PDF) of mass yields ai for volatility bins (Ci* = 0.1, 1, 10,
100) for one low RH (No. 4, left panel) and one high RH (No. 3, right panel) experiment.
6.4 Discussion
A key parameter for yield parameterization, shown in Figure 6.5, is the estimation of the
absorptive mass, COA. Traditionally, COA is considered equal to the total OA mass and the
inorganic fraction is not considered to take part in the partitioning, which is consistent with
our observations (Sect. 6.3). As mentioned above, a great part of the organic mass occurs
within the particle population with a small inorganic fraction and the yields do not exhibit a
significant correlation with the inorganic aerosol mass. We suggest that even organic
compounds present in the same particles as the inorganic seed (mode2, Figure 6.4) are likely
to form 2 separate phases: an organic-rich phase and an electrolyte-rich phase. We recognize
that experimental determinations of liquid-liquid phase separation are lacking, but as shown
in the literature, mixing between sulfate and organic compounds only occur at very high RH
and for highly oxygenated compounds (O:C > 0.8; You et al., 2013). Therefore, we will
consider the organic phase, i.e. OA and the bounded water, to represent the absorptive mass.
6.4 Discussion 91
For the hydrophobic seed, its mixing properties with of SOA component are unknown and
hence experiments using this seed will not be included in the yield parameterization.
Products formed early after the oxidation started own two properties due to their high O : C:
1) They have a very low volatility and ability to stick at their first collision and thus
heterogeneous nucleation onto the surface occurs in the beginning of an experiment. 2) They
have a high miscibility with inorganic solutions and thus mixing with the prevailing seed can
occur in the beginning of an experiment. As these products stay in the aerosol phase and do
not evaporate they provide more absorptive mass for further products to partition in, which is
larger for higher relative humidity due to the hygroscopic behaviour.
The influence of the seed on the yield due to varying acidity or LWC remains to be fully
elucidated (i.e., to what extent: y(acidic seed) > y(neutral seed) > y(CF-seed)]. For higher
yields under acidic conditions no increasing effect on organics in mode2 is observed, while
this could have been related to a better mixing behavior of NH4HSO4 (You et al., 2013) and
H2SO4 at high RH. If absorptive partitioning is dominant, organics dilute efficiently in the
liquid phase; their concentration in the particle phase is lower for high LWC than for lower
LWC and their low partial pressure causes more uptake of organics, which in turn causes
more uptake of water. This feed-back reaction drives the uptake and provides even for the
small hygroscopic growth factors of organics a significant water volume. Cocker et al. (2001)
found a small RH effect studying α-pinene ozonolysis reaching up to 300 µg m-3 organic and
water concentrations, while few data points at mass concentrations 0-35µg m-3 and NH4HSO4
seed might even indicate an increase in yield compared to (NH4)2SO4. Also in Cocker et al.
(2001) little RH effect on very high SOA loadings was seen, following Pankow et al. (2010).
At high SOA loadings, all condensable products might already have condensed. We conclude
that low, atmospherically relevant organic mass concentrations were necessary to elucidate
the RH effect seen in this study.
Concerning miscibility, the mixing state of the aerosol might be a function of particle size.
When condensing α-pinene reaction products onto the CF-seed, there’s no measurable change
in the exponential decay of CF-related ions (e.g. CF3) in the HR-ToF-AMS measurement.
This indicates that the CF-seed doesn’t mix with α-pinene SOA, because otherwise it would
slow down the decrease of the CF-seed or even increase its suspended mass concentration by
partitioning effects.
At longer exposures to OH, SOA products increase in degree of oxygenation and their ability
to mix with the inorganic solutions might increase (You et al., 2013). Liquid-liquid phase
92 6 The link between organic aerosol mass loading and degree of oxygenation
separation could decrease organic partitioning because organic layers of different viscosity
inhibit fast diffusion and limit feedback uptake due to poorly mixed organic layers.
6.5 Conclusions
SOA yields from the photooxidation of α-pinene at low (~ 25 %) and high (~ 60 %) relative
humidity (RH), various NOx/VOC ratios (0.04–3.8) and with different seed chemical
compositions (sulfate-containing or hydrophobic carbon) were studied in controlled SC
experiments. High RH increased SOA yields up to five times compared to low RH, with
greater increases for the most hygroscopic/acidic seeds. While many aqueous phase studies
suggest a major effect of the relative humidity on the chemical composition via e. g.
oligomerisation, in this study, most of the organic products are unlikely to mix with the
prevailing seeds (nonpolar organic or polar inorganic) and the chemical composition of SOA
is mainly influenced by the NOx/α-pinene ratio via gas-phase reactions.
Yields presented here compare well with literature yields from α-pinene ozonolysis ranging
up to ~0.18 for 30 µg m-3 organic mass concentration summarized by Hao et al. (2011),
measured at typical laboratory temperatures (~25 ± 5 °C). In this study, yields at NOx/VOC
ratios < 0.1 were 2–11 times higher compared to yields at NOx/VOC ratios of up to 3.8. This
NOx dependence follows the same trend as seen in previous studies for α-pinene SOA (Ng et
al., 2007). Presto et al. (2005) found a factor up to 4 for ratios above 0.67 NOx/α-pinene. The
chemical signature, investigated in Van Krevelen diagrams, showed a main influence from the
NOx/VOC ratio. For the same equivalent OH (hydroxyl radical) exposure, experiments at low
NOx/VOC ( < 0.1) ratios formed products with higher H : C while experiments with higher
NOx/VOC ( > 1) showed lower H : C. This is expected from higher formation yields of
hydroxyl functional groups and peroxides at low NOx. We present wall-loss-corrected yields
as a function of absorptive masses combining organics and the bound liquid water content.
We parameterize the volatility distributions for the use in modelling studies. This study
clearly presents different yields for the same reacted α-pinene concentration for varying
experimental conditions. This might also occur in the ambient atmosphere, such that SOA
loadings are sensitive to slight changes in the absorptive mass concentration. The NOx/VOC
ratio and relative humidity have to be considered in models to accurately predict SOA yields.
6.5 Conclusions 93
Acknowledgements. This work has been supported by the EU 7th Framework projects
EUROCHAMP-2 and PEGASOS, as well as the Swiss National Science Foundation
(Ambizione PZ00P2_131673, SAPMAV 200021_13016), the EU commission (FP7,
COFUND: PSI-Fellow, grant agreement n.° 290605). We thank Rene Richter and Günther
Wehrle for their technical support at the smog chamber, and in addition Michel J. Rossi,
Martin Gysel, Andy Zünd, Neil Donahue and Barbara Turpin for the helpful discussions.
94 6 The link between organic aerosol mass loading and degree of oxygenation
6.6 Supplementary material
6.6.1 Transmission and collection efficiency correction
During experiments 9, 10, 12 and 14-17, the transmission efficiency of one of the two PM2.5
lenses used in the HR-ToF-AMS was weak for particles up to vacuum aerodynamic diameters
(dva) of 230 nm, the region were the organic : sulfate ratio is highest. The not-transmitted
aerosol was accounted for by means of HR-ToF-AMS and SMPS comparison. The sulfate
seed and CF-seed mass distributions were captured well within the measurement region by
both, AMS and SMPS. The seed volume Vseed was determined by applying the loss rate of the
CF-seed (kCF) or sulfate seed (kSO4), respectively, to the measured initial SMPS volume Vinitial:
∙ exp or ∙ exp (S 6.1)
The additionally formed organic volume ΔVSMPS was derived from the difference of total and
seed volume (∆VSMPS = Vtotal - Vseed). The method is displayed in Figure S 6.1. The collection
efficiency of organics (CEorg) in the AMS in turn was determined by the ratio of Vorg and
∆VSMPS shown in Figure S 6.2. HR-ToF-AMS mass concentrations divided by the
corresponding densities of the species yielded the AMS volume. CEorg was ~ 0.55 for
experiments 12 and 14 with lower RH and ~ 0.75 for experiments 9 and 10 with higher RH.
The CF-seed experiments showed CEorg of 1.
The remaining experiments were conducted with the second PM2.5 lens with good
transmission efficiency at lower dva. The SMPS upper diameter cut off for expts. 1–6 was set
to 600 nm mobility diameter instead of the standard 1000 nm in this study and thus the AMS
volume even exceeded the SMPS volume. Therefore, a CEorg of 1 was assumed for
experiments 1–6. The CEorg for experiments 7, 8, 11 and 13 were between 0.7–0.9. All
organic mass concentrations given in this study are corrected by dividing by the collection
efficiency, summarized in Table S 6.2.
6.6 Supplementary material 95
Figure S 6.1. Measured SMPS volume (thin line), estimated CF-seed volume (dashed line, with decay rate kCF determined from AMS data) and the difference of both, ΔVSMPS (thick line), as a function of time after lights on. ΔVSMPS corresponds to the secondary organic volume formed.
Figure S 6.2. Comparison of 20-minutes averaged volumes ΔVSMPS and VAMS (=Vorg). ΔVSMPS (= difference between total SMPS volume Vtotal and estimated SO4 volume). Legend contains information on which instrument was taken as reference.
96 6 The link between organic aerosol mass loading and degree of oxygenation
6.6.2 Seed composition
Figure S 6.3 shows the temporal evolution of NH4/SO4 in (moles/moles). Seen by the
different ratios and temporal evolution, the experiments were performed with different seed
compositions even when nebulizing always the same concentration (1g L-1) of NH4HSO4
solution in ultrapure milli-Q water. We estimated that 1 ppb of gaseous NH3 was needed to
neutralize 4 µg m-3 NH4HSO4 to (NH4)2SO4 using the following formula:
∙
∙ ∙ . ∙
/1ppb (S 6.2)
Where cNH3 is the concentration of NH3, Vmol is the molar volume, mSO4 the mass
concentration of SO4 and MSO4 the molar mass of SO4.
During experiments 1-6, the molar NH4/SO4 ratios represent acidic seed conditions. We claim
that this is due to a higher concentrated H2SO4 solution (0.1 M) serving the HONO source. A
volume as low as 0.1 µL of the 0.1 M H2SO4 solution would be sufficient to convert even the
highest seed concentration of liquid (NH4)2SO4 in the 27 m³ SC to NH4HSO4:
Assuming the highest seed concentration added to the chamber: 8 µg m-3 (NH4)2SO4 (=
6 × 10-8 mol m-³ (NH4)2SO4), scaled to the 27 m³ PSI smog chamber: 1.6 × 10-6 mol
(NH4)2SO4. To form NH4HSO4 from this, 1.6 × 10-6 mol H2SO4 = 1.6 × 10-4 g= 0.16 mg ≈
0.1 µL of pure H2SO4 would have to be injected to the chamber. 1 µL of our 0.1 M H2SO4
was most probably injected into the chamber.
The neutralization was confirmed by nebulization tests of (NH4)2SO4 and NH4HSO4 resulting
in apparent relative ionization efficiencies (RIE) of 1.1 and 0.55 for SO4, respectively, if no
chemical transformation is assumed. The RIE is defined as ionization efficiency (IE) of a
compound normalized to the IE of NO3 in the HR-ToF-AMS. Different RIEs for one
inorganic compound in the same HR-ToF-AMS are unlikely, rather point towards
neutralization of NH4HSO4 to (NH4)2SO4 between nebulizer and measurement.
6.6 Supplementary material 97
Figure S 6.3. Molar ratio of NH4 and SO4 as a function of time after lights on. Seed composition during experiments 1–6: SA & AHS due to significant concentration of H2SO4 added. During expts 7–14 the NH4HSO4 solution is partly neutralized to (NH4)2SO4 after nebulization.
98 6 The link between organic aerosol mass loading and degree of oxygenation
Figure S 6.4 shows the distinct mass spectrum of the fluorinated carbon seed (CF-seed)
aerosol. Table S 6.1 list the corresponding relative intensities compared to CF3 of each major
ion. The HR-ToF-AMS high resolution analysis is a good tool to distinguish between α-
pinene SOA and the CF-seed ion peaks in the mass spectrum. The decay rates of the CF-seed
concentration in the smog chamber could thus easily be estimated by fitting the sum of three
main ions (CF2, CF3, C2F3O).
Figure S 6.4. Mass spectrum of CF-seed measured with HR-ToF-AMS normalized to CF3 (ion with highest intensity).
Table S 6.1. Mass spectrum of CF-seed measured with HR-ToF-AMS normalized to CF3 (ion with highest intensity).
m/z Ion formula Normalized intensity
28 CO 0.130
31 CF 0.097
44 CO2 0.130
50 CF2 0.041
69 CF3 1.000
97 C2F3O 0.110
100 C2F4 0.094
119 C2F5 0.506
131 C3F5 0.113
m/z Ion formula Normalized intensity
147 C3F5O 0.130
150 C3F5 0.085
169 C3F7 0.762
185 C3F7O 0.013
235 C4F9O 0.010
285 C5F11O 0.041
297 C6F11O 0.010
335 C6F13O 0.032
6.6 Supplementary material 99
6.6.3 Additional figures and table
Table S 6.2. List of wall-loss-correction parameters and collection efficiencies applied to each experiment.
No 1/τ CForg
1 0.17 1
2 0.11 1
3 0.13 1
4 0.16 1
5 0.11 1
6 0.17 1
7 0.13 0.78
8 0.13 0.70
9 0.11 0.75
10 0.13 0.75
11 0.13 0.89
12 0.16 0.55
13 0.13 0.80
14 0.10 0.55
15 0.18 1
16 0.18 1
17 0.18 1
100 6 The link between organic aerosol mass loading and degree of oxygenation
Figure S 6.5. Molar concentrations of nitrate (NO3) as a function of molar concentration of carbon (C) for all experiments with hygroscopic seed. High NOx experiments follow a ratio of approximately 1:30, low NOx experiments a ratio of approximately 1:100. The two arrows indicate that NO3:C changes its slope when the initially high NOx concentration decayed to low values in the end of high NOx experiments 1, 2 and 3.
Figure S 6.6. 20-min-averaged organic mass concentration as a function of time after lights on. Traces were fit with an exponential between 5 and 8 h after lights on to determine wall loss rate. Wall loss decay rates for experiments with too short fit period were replaced by the mean 1/τ-value of 0.13 (dashed lines) and 0.18 (dotted lines).
6.6 Supplementary material 101
Figure S 6.7. 20-min-averaged wall-loss-corrected yield as a function of reacted α-pinene. At the same concentration of α-pinene reacted, different yields are obtained due to various NOx/α-pinene ratios, relative humidities and seed compositions. Traces are color coded for each experiment according to Table 1 in the main text. Asterisks indicate low NOx experiments.
Figure S 6.8. 20-min-averaged fraction of oligomers (m/z > 150) of the total organic mass concentration as a function of OH exposure. Symbols indicate the seed composition, colors indicate the respective experiment as given in the legend
Figure S 6.9. Evolution of size distributions. Measured organic, SO4, NH4, NO3 mass distributions for OH exposures of 0×, (0.5 ± 0.2)×, (1.0 ± 0.3)× and (2.0 ± 0.5) × 107 cm-3 h. Black lines represent estimated liquid water content (RH and individual GFs given for each expt., method described in main text). The calculated dry and wet surface distributions are shown on the right axes. Number of each experiment is given on the left edge (1, 5, 6).
6.6 Supplementary material 103
Figure S 6.10. 20-min averaged NO+/NO2+ ratio as a function of OH exposure compared to measured
NO+/NO2+ from calibration of NH4NO3 for each set of experiments.
Figure S 6.11. Total particle number concentration as a function of time after lights on. The increase after time = 0 is assumed due to an increased transmission efficiency of larger particles in the lines before the condensation particle counter measurement.
104 6 The link between organic aerosol mass loading and degree of oxygenation
6.6 Supplementary material 105
Figure S 6.12. Probability density functions (PDF) of mass yields ai for volatility bins (c*=0.1, 1, 10, 100) to solve Eq. (6.10) in the main text. Experiment number is given in the legend.
___________________________________________________________________________
7 VIsible light Photosensitized Secondary
Organic Aerosol evolution (VIPSOA)
___________________________________________________________________________
108 7 VIsible light Photosensitized Secondary Organic Aerosol evolution (VIPSOA)
7.1 Introduction and scientific objective
The direct interaction of radiation with particles might have an effect on their chemical
composition. Stemmler et al. (2006) found a conversion of nitrogen dioxide (NO2) to nitrous
acid (HONO) induced by visible light (400–700 nm) irradiation of humic acid films covering
the surface of a flow reactor. D'Anna et al. (2009) showed that near-ultraviolet and visible
irradiation initiated ozone removal on the surface of humic acid aerosol and coated wall flow-
tube systems. Monge et al. (2012) found that UV-A (315–380 nm) irradiation of gas-phase
isoprene and the internally mixed seed containing humic acid (HA), succinic acid and
NH4NO3(1∶10∶1 in weight) in pure air led to particle growth and control experiments showed
that the photosensitizer HA is required for this process. Those newly identified pathways of
photoinduced SOA formation and growth are suggested to be caused by the formation of
radicals and singlet oxygen at the surface of the seed aerosol that can react with VOC
impinging on the surface (Monge et al., 2012).
The oxidation state of a particle can be increased in a number of ways. First, the oxidation of
volatile organic compounds (VOC) by OH radicals in the gas-phase results in products with
lower saturation vapour pressures, which can condense on pre-existing particles (Figure 7.1a).
This process increases the total aerosol mass as well as the average O : C ratio, while in the
following processes mainly the O : C ratio is affected. Second, semi-volatile compounds may
evaporate from the surface, oxidize in the gas phase and re-condense again after the reaction,
while the carbon mass stay constant (Figure 7.1b). Third, OH radicals may react directly on
the surface of the particles (Figure 7.1c). Forth, an O : C increase may happen by radiation
entering the particle and initiating formation of OH radicals and oxidation within the particle
(Figure 7.1d). This last mentioned process is the subject of the present study. Photosensitizers,
chemical substances that absorb light, cause photochemical reactions via energy transfer and
exchange of electrons or protons, but don’t react themselves might be important in this
respect. Compounds included in the particle can turn into photosensitizers causing
photochemical reactions within the particle. Visible light (wavelength λ > 400 nm), which
excludes photolysis of gases and thus ozone and OH radical formation, on the chemical
composition of organic aerosol might play a non-negligible role. These experiments were
performed in collaboration with the group of Dr. Markus Ammann at PSI.
7.2 Method 109
Figure 7.1. Schematic of possible processes leading to an increase of the oxidation state of organic aerosols in the atmosphere. (VOC = volatile organic compound, OH = hydroxyl radical)
7.2 Method
During the ‘VIsible light Photosensitized Secondary Organic Aerosol evolution’ (VIPSOA)
study, wood burning (WB) emissions and known pure chemical compounds served as “real”
and “model” system, respectively.
For the introduction of wood burning emissions into the PSI smog chamber (SC; see Sect.
4.1.) the identical setup as described in detail in Heringa et al. (2011) was used involving a
modern logwood burner Attika Avant (year of manufacture: 2009), a heated ejector diluter
(Dekati Ltd., Tampere, Finland) and heated inlet lines (150 °C) to prevent condensation
(Figure 7.2). The gas phase and aerosol phase were monitored with a number of instruments
described in detail in Sect. 4.2: a CPC and an SMPS for the physical aerosol properties, and
an HR-ToF-AMS for the aerosol chemical composition, and O3 and NOx monitors for the gas-
phase composition.
In the “model” system, 112 µL (≈1000 ppb) liquid-phase cyclohexanol (double-bound
alcohol) was injected via the heated (T = 80 °C) glass bulb with 10 L min-1 flush and
10 L min-1 dilution flow into the smog chamber to serve as SOA precursor. A suspension of
the photosensitizer methylene blue (0.05 g L-1; light absorption between λ = 550–700 nm with
the maximum at λ = 656 nm) and ammonium sulfate (2 g L-1) in ultrapure milli-Q H2O was
nebulized with a pure air flow of 0.6 L min-1 and introduced in the smog chamber by addition
of a 10 L min-1 flush flow.
VOC+OH•
a) Exposure of gas phase VOC to OH radicals
OH• VOC
b) Oxidation and re-condensation of VOC
OH• VOC
b) Oxidation and re-condensation of VOC
OH•
c) Heterogeneous reaction on aerosol surface d) Solar radiation initiates reactions
110 7 VIsible light Photosensitized Secondary Organic Aerosol evolution (VIPSOA)
Figure 7.2. Schematic representation of the inlet system and smog chamber setup (Heringa et al., 2011, adapted).
All experiments were conducted at 50 ± 10 % relative humidity, 20–25 °C temperature and
after the standard smog chamber cleaning procedure described in Sect. 4.1. Four xenon arc
lamps installed in the chamber were covered with a UV blocking foil (METOLIGHT SFC-
10), resulting in a light spectrum with minor emission for λ < 400 nm. This setup is referred to
as ‘visible light’ hereafter. During experiments for the “model” system visible light was used
as radiation source, while during the wood burning experiments standard xenon arc lamps and
black lights mounted underneath the smog chamber bag to accelerate reactions were used to
activate the primary wood burning aerosol ahead of visible light and dark periods. A
comparison of the visible (xenon arc lamps covered with UV filter foil METOLIGHT SFC-
10), standard xenon (covered with fluorinated ethylene propylene (FEP) films on glass
filters), black (Cleo performance, 100W) and direct sun light spectra is shown in Figure 7.3,
together with the transmission efficiency of the METOLIGHT foil.
7.3 Results 111
Figure 7.3. Spectral resolved light intensity of visible (xenon arc lamps covered with UV filter foil METOLIGHT SFC-10), standard xenon (covered with fluorinated ethylene propylene (FEP) films on glass filters), black (Cleo performance, 100W) and direct sun light.
7.3 Results
Experiments using the model compounds gas-phase precursor cyclohexanol (C6H10O), the
photosensitizer methylene blue (MB) and ammonium sulfate (AS) seed did not show an effect
of visible light on SOA, at least when switching approximately every two hours between dark
and light exposure times. Table 7.1 lists the procedures of one blank (10.5.2010) and one real
experiment (15.5.2010).
Table 7.1. System model for experiments with and without methylene blue (MB), ammonium sulfate (AS) and cyclohexanone (C6H10O) with visible light irradiation.
date AS MB C6H10O visible lights comments
10.05.2010 blank without methylene blue
15.05.2010 no mass production, no effect on f44
112 7 VIsible light Photosensitized Secondary Organic Aerosol evolution (VIPSOA)
The more realistic system of wood burning emissions was investigated during six experiments
of which light exposure and dark periods are chronologically listed in Table 7.2. After
injection of primary wood burning emissions to the PSI smog chamber, 2–7 h exposure of UV
light radiation (except exp. 6) led to formation of secondary organic aerosol, increased
concentration of ozone and decreased concentration of nitrogen oxide (NO) stemming from
the burning process. During experiments 1 and 2, after UV lights were switched off, the
existing ozone (O3) concentration was titrated away by the addition of a slightly higher
concentration of NO [O3+NO→NO2+O2]. Thus the oxidation with ozone is excluded for these
experiments, but NO3 chemistry could still be possible by the back reaction of N2O5 formed
during the dark period [NO3+NO2↔N2O5]. A slight decrease of NO and NO2 during visible
light exposure was observed. The evolutions of O3, NO and NO2 concentrations during each
period are listed as the start and end concentrations in Table 7.2.
Table 7.2. Observed changes in the temporal evolution of the organic mass fractionf44 of wood burning (WB) aerosol during darkness and different light exposure periods. The experiment description indicates whether titration of O3 by NO addition took place. The radiation types Xe = xenon lights (+BL = black lights), vis = visible lights (λ > 400 nm) and dark = no radiation are listed chronologically together with the exposure time. Experiment 6 is the only experiment without SOA formation by UV activation (visible light only). NO, NO2 and O3 concentration changes are given as start and end concentration per exposure time.
date No experiment radiation time slope f44 (fit) NO NO2 O3
description type h [% h-1] ppb ppb ppb
13.9.2010
WB with NO titration
Xe+BL 2 -0.6 ∆f44/∆t* 35-2 0-28 2.8-38
1 dark 20 0.04 ± 0.01 16-10 47-46 0
vis 5 0.15 ± 0.03 9-7 50 0
27.9.2010 2 WB with NO titration Xe+BL 2 -2.5 ∆f44/∆t* 84-10 16-66 0-23
dark 8 0.08 ± 0.01 10-8 123-119 0
26.8.2010 3 WB w/o NO titration
Xe+BL 5 0.47 ± 0.04 14-0.3 6-7 8-100
vis 14 0.12 ± 0.01 0 6-1.5 96-66
dark 9 0.04 ± 0.04 0 1.3-1.2 65-57
27.5.2010 4 WB w/o NO titration Xe 2 0.9 ∆f44/∆t* 86-11 8-57 7-22
vis 16 0.11 ± 0.01 0 70-40 6-7
23.9.2009 5+ WB w/o NO titration Xe 7 1.0 ∆f44/∆t* - - -
22.9.2010 6 WB visible light only vis 19 0.04 ± 0.02 0 6 ± 1 22-49
+) personal communication M. Heringa, PSI
*) ∆f44/∆t instead of fit due to a varying slope over time
7.3 Results 113
The evolution of the gas and aerosol phase for experiment 1 is displayed in Figure 7.4 (lower
panel), where the grey shaded areas represent light exposure periods (2 h xenon and black
lights, 20 h darkness, 5 h visible lights). Aerosol species organics, nitrate and ammonium and
gas-phase NO and O3 were injected with the WB emissions. SOA was formed, while O3 (and
NO2, not shown) increased and NO decreased during the UV light irradiation. NO injection
titrated all O3 and NO2 formed. During the dark period, aerosol species decreased due to wall
loss and a slight NO and NO2 decrease for unknown reason is observed. Once the visible
lights were switched on, the decrease in NO was steeper, while NO2 stayed constant. The
upper panel of Figure 7.4 shows the corresponding evolutions of the organic mass fractions
f44, f43 and their ratio. The chemical composition of primary wood burning emissions is quite
variable (Heringa et al., 2011) and in this case represented by a percentage of ~ 8 % for
organic mass 44 of total organics (f44) and 2 % f43. UV radiation led to reactions of the fresh
emissions and decreases f44 and f43 by condensation of newly formed semi-volatile organic
compounds. During the dark period, f44 increased with 0.04 % h-1 together with a loss of the
suspended organic mass concentration. Once the visible lights were switched on, the increase
in f44 was steeper, 0.15 % h-1, but also accompanied by a decrease in the NO concentration.
Figure 7.4. Temporal evolution of organic mass fractions f44, f43, their ratio org44/org43 (upper panel) and organics, NO3, SO4, NH4, with the NO and O3 concentrations (lower panel) as a function of time (expt. 1). Experimental procedure: SC filling with wood burning emissions, UV light irradiation, O3 titration with NO, dark period, visible light exposure.
114 7 VIsible light Photosensitized Secondary Organic Aerosol evolution (VIPSOA)
A comparison of the increase in organic mass fraction f44 during experiments 1 (UV, dark,
visible), 5 (UV only) and 6 (visible only) is shown in Figure 7.5 where a similarity of dark
(red) and visible light without prior UV ‘activation’ (green) periods and the less and less steep
increase in f44 during UV light exposure (xe, violet) can be seen.
Figure 7.5. Organic mass fraction f44 as a function of time after lights on for the three different radiation types: UV light only (violet), UV activation,
Furthermore, the change in the organic chemical composition during UV light exposure and
visible light exposure was investigated for the entire mass spectrum measured by the AMS
(see instrument Sect. 4.2). Figure 7.6a shows normalized organic mass spectra measured after
2 h and 5 h of UV light exposure (upper panel) and their difference mass spectrum (lower
panel) with main increases in m/z 18, 28, 44 and 58, and main decreases in m/z 29, 60 during
experiment 5. Figure 7.6b shows normalized organic mass spectra measured in the beginning
and after 15.5 h of visible light exposure (upper panel) and their difference mass spectrum
(lower panel) with main increases in m/z 18, 28, 44 and 58, and main decreases in m/z 15, 29,
31, 60 during experiment 4. All in all, very similar mass spectra and increases/decreases in the
same m/z were found. The chemical composition was similar, but the change in chemical
composition was slower under visible light and in the dark compared to UV light.
7.3 Results 115
Figure 7.6. (a) Normalized organic mass spectra measured after 2 h and 5 h of UV light exposure during experiment 5 and their difference mass spectrum (main increases in m/z 18, 28, 44 and 58, main decreases in m/z 29, 60). (b) Normalized organic mass spectra measured in the beginning and after 15.5 h of visible light exposure during experiment 4 and their difference mass spectrum (main increases in m/z 18, 28, 44 and 58, main decreases in m/z 15, 29, 31, 60).
116 7 VIsible light Photosensitized Secondary Organic Aerosol evolution (VIPSOA)
To summarize, first results indicate a measurable impact on particle oxidation, but no major
SOA production enhanced by visible light. The slope of the organic mass fraction f44 versus
time in the HR-ToF-AMS which is correlated to the O : C ratio showed significant differences
in the darkness and during visible light exposure. There are indications that an activation of
the wood burning aerosol by UV light exposure is needed to start the process that is prevailing
with visible light.
7.4 Measurement challenges and outlook
Despite promising results a comprehensive study of the effects of radiation on aerosol was
beyond the scope of this thesis. Additional parameters need to be investigated to be able to
draw final conclusions:
- The presence of OH radicals needs to be excluded by means of PTRMS (described in
Sect. 4.2) measurements. The slightest photolysis of e.g. HONO due to a small
fraction of short wavelength radiation in the light spectrum would lead to OH radical
formation.
- A possible temperature increase during visible light exposure periods could lead to
increased evaporation of particle phase organic compounds or could enhance
oxidizing reactions in the aerosol and thus lead to an increase in O : C. Conditions
could be kept more stable by decreasing the temperature setting of the air conditioning
system of the PSI smog chamber immediately prior to the visible light exposure
periods.
- Wall losses could be different due to increased turbulence initiated by the heat transfer
from the covered xenon lights to the smog chamber during light exposure compared to
darkness.
- The possible formation of N2O5 can be omitted if UV light exposure takes places
during O3 titration by NO.
- The measurement duration of 20 h and more is prone to possible contamination of air
entering the smog chamber through leaks. With the small scale changes observed,
contamination has to be minimized and well characterized.
7.4 Measurement challenges and outlook 117
The following technical ideas could minimize the OH radical concentration:
1. CO could be used as OH scavenger
2. Aerosol produced in the smog chamber could be isolated from the gas-phase by a
denuder and the effect of radiation onto the aerosol suspended in pure air could be
investigated by means of the PAM (potential aerosol mass, Kang et al., 2007)
chamber. Vice versa, aerosol could be produced in the PAM chamber, isolated from
the gas phase and then exposed to visible light in the smog chamber.
Finally, the matrix of the study could be extended to other systems such as α-pinene, diesel
emissions or suitable model compounds to draw general conclusions and suggest processes
that may change the chemical state of the aerosol by radiation.
___________________________________________________________________________
8 Final conclusions and outlook
___________________________________________________________________________
120 8 Final conclusions and outlook
The organic aerosol burden predicted by global “bottom-up” models used to be significantly
underestimated compared to ambient measurements, before a larger volatility range of organic
species and a more dynamic nature of POA and SOA in terms of volatility were allowed. This
meant a big step forward in understanding and predicting the aerosol burden and OA
formation processes. Smog chamber studies increase the knowledge of aerosol properties by
providing measurement data of isolated, well-controlled processes. SC experiments used to be
performed with very high mass loadings of hundreds of µg m-3, thought valid to be
extrapolated to low ambient concentrations. The presented work shows that this is however
not the case, because the chemical composition of α-pinene SOA is dependent on the organic
mass concentration, being more oxygenated at low organic mass loadings. For the first time,
LV-OOA-like aerosol from α-pinene was produced in a smog chamber by oxidation at typical
atmospheric OH concentrations. Based on these findings smog chamber studies must be
performed at near-ambient concentrations to accurately simulate ambient aerosol.
SOA is mainly formed by the oxidation of gas-phase precursors where SOA yield and
composition depend on the surrounding gas-phase mixture. Reactions in VOC-limited or
NOx-limited regimes yield products of very different chemical signature, and thus SOA
composition. In the atmosphere, NOx levels close to emission sources are high, being mainly
of anthropogenic origin. For this reason, we present data of α-pinene photooxidation SOA
formed under different NOx/α-pinene conditions and find a negative correlation of yield as a
function of NOx/α-pinene, given the same seed composition. This is in line with previous
studies.
Atmospheric water vapour is of special interest, given the fact that it is a greenhouse gas with
highly variable concentration in the atmosphere. Present as particulate water in the aerosol
phase, it changes refractive indices and influences the uptake of water-soluble or water-
insoluble organic compounds. For example, an increased uptake of water-soluble organic
compounds was found with increasing RH in the ambient atmosphere (Hennigan et al., 2009).
In this study, the impact of relative humidity on the yield and chemical composition of SOA
products from α-pinene photooxidation was studied in a set of SC experiments. SOA yields
were up to 6 times higher during experiments at high RH (~60 %) compared to low RH
(~25 %), while not significantly affecting the chemical signature, at least when using spectra
obtained from the Aerodyne aerosol mass spectrometer. This work elucidates how sensitive
SOA compositions and yields are to a variety of parameters, even when mainly focusing on α-
pinene as one single precursor.
7.4 Measurement challenges and outlook 121
A possible impact of direct radiation on the chemical composition of SOA formed by
oxidation of wood burning emissions in the PSI SC was suggested. This may be investigated
with a better controlled experimental setup, that could reveal if the radiation effects
previously measured in flow reactors are applicable to an environmental chamber and thus
more comparable to the atmosphere. In addition, well-chosen model systems to better pin
down the responsible mechanisms and systems, where no effect is expected, would complete
the study.
The impact of relative humidity on SOA from many more precursors than α-pinene should be
studied in the future. This study presents yields up to an organic mass concentration of 30
µg m-3. More experiments with similar seed composition, relative humidity and NOx/VOC
with an organic mass range extended to higher concentrations could help to clearly
distinguish yield curves for each condition as a function of absorptive mass concentration.
These parameterizations would show higher statistical robustness, advantageous also for
modellers.
Another question is, how the laboratory produced α-pinene SOA would behave in the
atmosphere when mixed with a constant miscible organic background aerosol. The
experiments include to some extent a self-enhancing feedback mechanism: when SOA is
condensed, more SOA will partition in return. This effect might be minimized in future
experiments by 1) performing experiments with constant, discriminable background COA and
observing if the newly formed SOA fraction still varies as a function of gas-phase
composition or 2) by aiming for similar SOA yields with well-balanced initial conditions.
___________________________________________________________________________
List of abbreviations and acronyms
___________________________________________________________________________
aci = aerosol-cloud interactions
AHS = ammonium hydrogen sulfate
ari = aerosol-radiation interactions
AS = ammonium sulfate
BC = black carbon
BVOC = biogenic volatile organic
compound
CF-seed = fluorinated hydrocarbon as seed
CF = fluorinated carbon
CPC = condensation particle counter
DMA = differential mobility analyzer
dva = vacuum aerodynamic diameter
ERF = effective radiative forcing
GF = growth factor
H : C = atomic hydrogen: carbon ratio
HONO = nitrous acid
HR-ToF-AMS = Aerodyne high resolution
time-of-flight aerosol mass
spectrometer
IPCC = Intergovernmental Panel on
Climate Change
LV-OOA = low-volatility oxygenated
organic aerosol
LWC = liquid water content
OA = organic aerosol
O : C = atomic oxygen: carbon ratio
OM = organic matter
PMx = particulate matter with aerodynamic
diameter smaller than x µm
POA = primary organic aerosol
PSI = Paul Scherrer Institute
RH = relative humidity
RIE = relative ionization efficiency
S = surface
SA = sulfuric acid
SC = smog chamber
SMPS = scanning mobility particle sizer
SOA = secondary organic aerosol
T = temperature
VBS = “volatility basis set”
VOC = volatile organic compound
V = volume
wlc = wall-loss-corrected
ZSR = Zdanovskii-Stokes-Robinson
___________________________________________________________________________
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___________________________________________________________________________
Acknowledgements
___________________________________________________________________________
I would like to thank...
... my doctoral advisor Prof. Urs Baltensperger for giving me the opportunity to do high-level
research in the Laboratory of Atmospheric Chemistry at PSI. With your constructive ideas
during Monday seminars, Urs and smog chamber meetings the work was always brought a
step forward. You showed interest and always gave very good input. Also, your effort to hold
the group together with LAC events made it nice to be part of the LAC besides the lab.
... Prof. Tom Peter who gave his support from the side of the Institute of Atmospheric and
Climate Science at ETH. The discussions during ETH interviews with questions from a more
distant view on the topic were inspiring.
... Dr. Harald Saathoff for taking the effort of being my external co-referee, coming to Zürich
and to review the Thesis. Thanks!
... Dr. André Prevôt who brought me to the LAC even without real project plan which allowed
us to flexibly follow promising research directions. Your input during scientific discussions
helped proceeding. Your openness and collegiality built a familiar environment.
... Dr. Josef Dommen to always ask critical questions which increased research quality by
much. ... Peter B. to go through all the effort during smog chamber experiments with me. The
two-way support was exceptional. Also the support of Arnaud, Manu, Carla and Emily
facilitated the experiments. ... Martin Gysel and Michel J. Rossi for fruitful discussions.
...Rene and Günther for support with the smog chamber hard ware ... Maarten, Claudia,
Torsten and Marie for introducing me to the LAC soft- and hard(ware) and much more. ...
Imad and Stephen who are inspiring discussion partners. ... the corridor-group: Kathrin,
Monica, Francesco, Robert, Kaspar and Suzanne for their collegiality. ... the LAC-band
through which I started singing again! ... Pete Sampras, Börni (sorry), Fede and Emmi for
being just there. A special thank you goes to Dani and the rest of my family for being the
greatest supporters!
___________________________________________________________________________
Curriculum vitae
___________________________________________________________________________
Lisa Pfaffenberger, born on 29th of January 1985 in Bad Tölz, Germany
Education
04/2010 – 03/2014 PhD, Laboratory of Atmospheric Chemistry, Paul Scherrer Institute,
Villigen, Switzerland
10/2004 – 10/2009 Studies of Meteorology (Diploma, Ludwig-Maximilians-University
Munich, Germany and Universitetet i Bergen, Norway
Diploma Thesis, Deutsches Zentrum für Luft- und Raumfahrt,
Oberpfaffenhofen, Germany
Topic: “Particle emissions from shipping and their impact on the
aerosol of the marine boundary layer – Results of the QUANTIFY
SHIPS Study 2007“
09/1995 – 05/2004 High School, Gymnasium Unterhaching, Germany, Abitur (A-Level)
Platform Presentations
09/2013 European Aerosol Conference, Prague, Czech Republic
“Dependence of α-pinene secondary organic aerosol formation on relative
humidity and aerosol surface distribution”
09/2012 European Aerosol Conference, Granada, Spain
“Is the chemical composition of α-pinene secondary organic aerosol dependent
on particulate water content?”
10/2011 American Association For Aerosol Research Conference, Orlando, USA
“How to produce low-volatility oxygenated organic aerosol“
09/2009 European Aerosol Conference, Karlsruhe, Germany
“From fresh exhaust to CCN: Transformation of particles from shipping“
136 Curriculum vitae
Peer reviewed publications
Two-stroke scooters are a dominant source of air pollution in many cities
Platt, S. M., El Haddad, I., Pieber, S. M., Huang, R.-J., Zardini, A. A., Clairotte, M., Suarez-Bertoa,
R., Barmet, P., Pfaffenberger, L., Wolf, R., Slowik, J. G., Fuller, S. J., Kalberer, M., Chirico, R.,
Dommen, J., Astorga, C., Zimmermann, R., Marchand, N., Hellebust, S., Temime-Roussel, B.,
Baltensperger U. and Prévôt, A. S. H.
Nature Communications, 5, 3749, 2014, doi:10.1038/ncomms4749
Modeling the evolution of aerosol particles in a ship plume using PartMC-MOSAIC
Tian, J., Riemer, N., West, M., Pfaffenberger, L., Schlager, H., and Petzold, A., 2014
Atmos. Chem. Phys., 14, 5327-5347, 2014, doi:10.5194/acp-14-5327-2014
Online measurements of water-soluble organic acids in the gas and aerosol phase from the
photooxidation of 1,3,5-trimethylbenzene
Praplan A. P., Hegyi-Gaeggeler K., Barmet P., Pfaffenberger L., Dommen J. and Baltensperger U.
Atmos. Chem. Phys., 14, 8665-8677, 2014, doi:10.5194/acp-14-8665-2014
The link between organic aerosol mass loading and degree of oxygenation: An α-pinene
photooxidation study
Pfaffenberger, L., Barmet, P., Slowik, J. G., Praplan, A. P., Dommen, J., Prévôt, A. S. H., and
Baltensperger, U., 2013
Atmos. Chem. Phys., 13, 6493-6506, doi:10.5194/acp-13-6493-2013
Effective Henry’s Law Partitioning and the Salting Constant of Glyoxal in Aerosols Containing
Sulfate
Kampf, C. J., Waxman, E. M., Slowik, J. G., Dommen, J., Pfaffenberger, L., Praplan, A. P., Prévôt,
A. S. H., Baltensperger, U., Hoffmann, T. and Volkamer, R., 2013
Environ. Sci. Technol., 47, 4236-4244, doi:10.1021/es400083d
Similarities in STXM-NEXAFS Spectra of Atmospheric Particles and Secondary Organic
Aerosol Generated from Glyoxal, α-Pinene, Isoprene, 1,2,4-Trimethylbenzene, and d-Limonene
Shakya, K. M., Liu, S., Takahama, S., Russell, L. M., Keutsch, F. N., Galloway, M. M., Shilling, J. E.,
Hiranuma, N., Song, C., Kim, H., Paulson, S. E., Pfaffenberger, L., Barmet, P., Slowik, J., Prevot A.
S. H., Dommen, J. and Baltensperger, U., 2013
Aerosol Sci. Technol., 47, 543-555, doi:10.1080/02786826.2013.772950
Curriculum vitae 137
Presenting SAPUSS: Solving Aerosol Problem by Using Synergistic Strategies in Barcelona,
Spain
Dall'Osto, M., Querol, X., Alastuey, A., Minguillon, M. C., Alier, M., Amato, F., Brines, M., Cusack,
M., Grimalt, J. O., Karanasiou, A., Moreno, T., Pandolfi, M., Pey, J., Reche, C., Ripoll, A., Tauler, R.,
Van Drooge, B. L., Viana, M., Harrison, R. M., Gietl, J., Beddows, D., Bloss, W., O'Dowd, C.,
Ceburnis, D., Martucci, G., Ng, N. L., Worsnop, D., Wenger, J., Mc Gillicuddy, E., Sodeau, J., Healy,
R., Lucarelli, F., Nava, S., Jimenez, J. L., Gomez Moreno, F., Artinano, B., Prévôt, A. S. H.,
Pfaffenberger, L., Frey, S., Wilsenack, F., Casabona, D., Jiménez-Guerrero, P., Gross, D., and Cots,
N., 2013
Atmos. Chem. Phys.,13, 8991-9019, doi:10.5194/acp-13-8991-2013
Development of a sensitive long path absorption photometer to quantify peroxides in aerosol
particles (Peroxide-LOPAP)
Mertes, P., Pfaffenberger, L., Dommen, J., Kalberer, M., and Baltensperger, U., 2012
Atmos. Meas. Tech., 5, 2339-2348, doi:10.5194/amt-5-2339-2012
A new method to discriminate secondary organic aerosols from different sources using high-
resolution aerosol mass spectra
Heringa, M. F., DeCarlo, P. F., Chirico, R., Tritscher, T., Clairotte, M., Mohr, C., Crippa, M., Slowik,
J. G., Pfaffenberger, L., Dommen, J., Weingartner, E., Prévôt, A. S. H., and Baltensperger, U., 2012
Atmos. Chem. Phys., 12, 2189-2203, doi:10.5194/acp-12-2189-2012
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Villigen, September 12, 2014