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Atmos. Chem. Phys., 17, 15181–15197, 2017

https://doi.org/10.5194/acp-17-15181-2017

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The role of ions in new particle formation in the CLOUD chamber

Robert Wagner

, Chao Yan

, Katrianne Lehtipalo

1,2

, Jonathan Duplissy

, Tuomo Nieminen

, Juha Kangasluoma

Lauri R. Ahonen

, Lubna Dada

, Jenni Kontkanen

1,5

, Hanna E. Manninen

1,6

, Antonio Dias

6,7

, Antonio Amorim

7,8

Paulus S. Bauer

, Anton Bergen

, Anne-Kathrin Bernhammer

, Federico Bianchi

, Sophia Brilke

9,10

Stephany Buenrostro Mazon

, Xuemeng Chen

, Danielle C. Draper

, Lukas Fischer

, Carla Frege

, Claudia Fuchs

Olga Garmash

, Hamish Gordon

6,13

, Jani Hakala

, Liine Heikkinen

, Martin Heinritzi

, Victoria Hofbauer

Christopher R. Hoyle

, Jasper Kirkby

6,10

, Andreas Kürten

, Alexander N. Kvashnin

, Tiia Laurila

Michael J. Lawler

, Huajun Mai

, Vladimir Makhmutov

15,17

, Roy L. Mauldin III

1,18

, Ugo Molteni

Leonid Nichman

19,20,21

, Wei Nie

1,22

, Andrea Ojdanic

, Antti Onnela

, Felix Piel

10,23

, Lauriane L. J. Quéléver

Matti P. Rissanen

, Nina Sarnela

, Simon Schallhart

, Kamalika Sengupta

, Mario Simon

, Dominik Stolzenburg

Yuri Stozhkov

, Jasmin Tröstl

, Yrjö Viisanen

, Alexander L. Vogel

2,6

, Andrea C. Wagner

, Mao Xiao

Penglin Ye

14,20

, Urs Baltensperger

, Joachim Curtius

, Neil M. Donahue

, Richard C. Flagan

, Martin Gallagher

Armin Hansel

11,23

, James N. Smith

4,12

, António Tomé

, Paul M. Winkler

, Douglas Worsnop

1,3,20,25

, Mikael Ehn

Mikko Sipilä

, Veli-Matti Kerminen

, Tuukka Petäjä

, and Markku Kulmala

Department of Physics, University of Helsinki, Helsinki, Finland

Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, Villigen, Switzerland

Helsinki Institute of Physics, University of Helsinki, P.O. Box 64, Helsinki, Finland

University of Eastern Finland, Department of Applied Physics, P.O. Box 1627, Kuopio, Finland

Department of Environmental Science and Analytical Chemistry (ACES) & Bolin Centre for Climate Research, Stockholm

University, Stockholm, Sweden

CERN, Geneva, Switzerland

CENTRA – SIM, University of Lisbon and University of Beira Interior, Lisbon, Portugal

Faculty of Science and Technology, New University of Lisbon, Lisbon, Portugal

University of Vienna, Faculty of Physics, Vienna, Austria

Goethe University Frankfurt, Institute for Atmospheric and Environmental Sciences, Frankfurt am Main, Germany

Institute for Ion and Applied Physics, University of Innsbruck, Innsbruck, Austria

Department of Chemistry, University of California, Irvine, CA, USA

University of Leeds, School of Earth and Environment, Leeds, UK

Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, USA

Lebedev Physical Institute, Russian Academy of Sciences, Moscow, Russia

California Institute of Technology, Pasadena, CA, USA

Moscow Institute of Physics and Technology (State University), Moscow, Russia

Department of Atmospheric and Oceanic Sciences, Boulder, Colorado

School of Earth and Environmental Sciences, University of Manchester, Manchester, UK

Aerodyne Research Inc., Billerica, MA, USA

Department of Chemistry, Boston College, Chestnut Hill, MA, USA

Joint International Research Laboratory of Atmospheric and Earth System Sciences, Nanjing University, Nanjing, China

IONICON Analytik GmbH, Innsbruck, Austria

Finnish Meteorological Institute (FMI), P.O. Box 503, Helsinki, Finland

TOFWERK AG, Uttigenstrasse 22, Thun, Switzerland

Correspondence:

Markku Kulmala (markku.kulmala@helsinki.fi)

Received: 8 June 2017 – Discussion started: 17 July 2017

Revised: 8 November 2017 – Accepted: 12 November 2017 – Published: 21 December 2017

Published by Copernicus Publications on behalf of the European Geosciences Union.

15182

R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

Abstract.

The formation of secondary particles in the atmo-

sphere accounts for more than half of global cloud conden-

sation nuclei. Experiments at the CERN CLOUD (Cosmics

Leaving OUtdoor Droplets) chamber have underlined the im-

portance of ions for new particle formation, but quantify-

ing their effect in the atmosphere remains challenging. By

using a novel instrument setup consisting of two nanopar-

ticle counters, one of them equipped with an ion filter, we

were able to further investigate the ion-related mechanisms

of new particle formation. In autumn 2015, we carried out

experiments at CLOUD on four systems of different chem-

ical compositions involving monoterpenes, sulfuric acid, ni-

trogen oxides, and ammonia. We measured the influence of

ions on the nucleation rates under precisely controlled and

atmospherically relevant conditions. Our results indicate that

ions enhance the nucleation process when the charge is nec-

essary to stabilize newly formed clusters, i.e., in conditions

in which neutral clusters are unstable. For charged clusters

that were formed by ion-induced nucleation, we were able

to measure, for the first time, their progressive neutralization

due to recombination with oppositely charged ions. A large

fraction of the clusters carried a charge at 1.5 nm diameter.

However, depending on particle growth rates and ion concen-

trations, charged clusters were largely neutralized by ion–ion

recombination before they grew to 2.5 nm. At this size, more

than 90 % of particles were neutral. In other words, particles

may originate from ion-induced nucleation, although they are

neutral upon detection at diameters larger than 2.5 nm. Ob-

servations at Hyytiälä, Finland, showed lower ion concentra-

tions and a lower contribution of ion-induced nucleation than

measured at CLOUD under similar conditions. Although this

can be partly explained by the observation that ion-induced

fractions decrease towards lower ion concentrations, further

investigations are needed to resolve the origin of the discrep-

ancy.

1 Introduction

Aerosol particles influence our life in various ways by af-

fecting our health, the water cycle, and the global climate.

The climate effect of aerosols is still poorly understood and

contributes a large part of the uncertainty when estimat-

ing Earth’s radiative forcing (IPCC, 2013). Aerosols can

influence the radiative forcing directly by absorbing and

scattering sunlight. Furthermore, when aerosol particles act

as cloud condensation nuclei, they affect cloud brightness

and lifetime (Albrecht, 1989). In addition to direct emis-

sion from sources such as combustion processes, volcanoes,

or sea spray, aerosols are also produced in the atmosphere

from condensable vapors via so-called new particle forma-

tion (NPF; Kulmala et al., 2004).

During the initial step of NPF, also known as particle nu-

cleation, ions can play an important role by enhancing the

stability of newly formed molecular clusters (Yu and Turco,

2001) and reducing their evaporation rates. Key factors deter-

mining the influence of ions are the concentration of precur-

sor vapors (Kulmala et al., 2014), the condensation sink of

preexisting particles (Kerminen et al., 2001; Kulmala et al.,

2014), temperature (Kürten et al., 2016), and the ionization

rate from galactic cosmic rays and terrestrial radioactivity

such as radon (Zhang et al., 2011).

The term “ion-induced nucleation” refers to the ion-

assisted formation of thermodynamically stable particles,

i.e., for which the growth rate exceeds the evaporation rate.

Nucleation occurs at the critical size or, in the case of bar-

rierless nucleation, upon dimer formation. The ion either di-

rectly stabilizes the molecular cluster or helps the embryonic

charged cluster exceed the stable size by recombination with

an oppositely charged cluster, which neutralizes the charge.

To allow for the latter mechanism, Yu and Turco (2001), in-

troduced the term “ion-mediated nucleation”. Here we will

refer to both processes collectively as ion-induced nucleation

for consistency with earlier publications from the CLOUD

(Cosmics Leaving OUtdoor Droplets) project. Early labora-

tory measurements suggested that ion-induced nucleation of

sulfuric acid particles would be important in the low temper-

atures of the middle and upper troposphere, but not apprecia-

ble in the boundary layer (Lovejoy et al., 2004; Curtius et al.,

2006).

While some models predict a large contribution of ion-

induced nucleation to aerosol particles in the global tropo-

sphere (Kazil et al., 2010; Yu et al., 2010), atmospheric ob-

servations in the boundary layer indicated only minor con-

tributions from ion-induced nucleation (Gagne et al., 2008;

Kontkanen et al., 2013; Kulmala et al., 2010, 2013; Manni-

nen et al., 2010, 2009). However, by using kinetic modeling

and simplified analytical analysis of progressive neutraliza-

tion during particle growth, Yu and Turco (2011) provided

a different interpretation of these atmospheric observations.

They concluded that a major contribution of ion-induced nu-

cleation cannot be ruled out. Furthermore, they concluded

that the observations suggest that the ion-induced nucleation

pathway may be dominant.

The signature of ion-induced nucleation in the atmosphere

is the appearance and growth of charged molecular clusters

just above the size range of small ions. Here we will refer to

particles measured above a certain detection threshold as par-

ticle

formation

, whereas we use particle

nucleation

to refer

to the formation of thermodynamically stable particles above

the critical size. Measurements in the boundary layer at the

boreal forest site in Hyytiälä, Finland, suggested that ion-

induced nucleation contributes around 10 % to total new par-

ticle formation between 2 and 3 nm (Manninen et al., 2009).

At sites at higher altitude like Pallas, Finland, or Jungfrau-

Atmos. Chem. Phys., 17, 15181–15197, 2017

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R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

15183

joch, Switzerland, the contribution of charged particle for-

mation was found to be up to 20–30 % (Boulon et al., 2010;

Manninen et al., 2010; Kulmala et al., 2013; Rose et al.,

2015; Bianchi et al., 2016). In Antarctica, a contribution of

30 % was reported (Asmi et al., 2010). From these mea-

surements, it could be inferred that ion-induced nucleation

makes only a minor contribution to new particle formation in

the boundary layer. However, following ion-induced nucle-

ation, the charged particles are progressively neutralized by

recombination with oppositely charged particles. This pro-

cess, known as ion–ion recombination, needs to be accounted

for before the ion-induced nucleation rate can be determined.

The rate at which recombination takes place depends on con-

ditions such as ion concentrations, temperature, and humid-

ity (Franchin et al., 2015). The studies estimating the num-

ber of recombination-originating neutral clusters using mea-

sured ion concentrations have found that very low fractions

(0–13 %) of clusters formed via recombination compared to

total cluster concentrations (Lehtipalo et al., 2009; Manninen

et al., 2009; Kontkanen et al., 2013; Kulmala et al., 2013).

The CLOUD experiment measures the ion-induced nu-

cleation rate directly, excluding uncertainties due to subse-

quent neutralization of the charged clusters by ion–ion re-

combination. The method is to compare the nucleation rate

measured when high-voltage electrodes inside the chamber

(Sect. 2.1) are switched on, which rapidly clears out all ions,

with the nucleation rate measured with the electrodes set to

0 V (ground potential; Kirkby et al., 2011). The difference

of these two measurements gives the ion-induced nucleation

rate due to galactic cosmic rays (GCRs) that traverse the

chamber.

The first results from CLOUD indicated that new particle

formation involving sulfuric acid, ammonia, and water was

significantly enhanced by GCR ionization, given that nucle-

ation rates are lower than the limiting ion pair production

rate of about 4 cm

−

(Kirkby et al., 2011). In contrast,

ion-induced nucleation played only a minor role for parti-

cles involving sulfuric acid, dimethylamine, and water, due

to the high stability (low evaporation rates) of neutral molec-

ular clusters in this case (Almeida et al., 2013; Kürten et al.,

2014). A dominant role of ion-induced nucleation was found

over a wide range of free tropospheric temperatures (249–

299 K) for both binary and ternary inorganic particles in-

volving sulfuric acid, ammonia, and water (Duplissy et al.,

2016). In the case of the recently discovered nucleation of

pure biogenic particles, ion-induced nucleation contributed

significantly to the total nucleation rate, again up to the limit

imposed by the ionization rate (Kirkby et al., 2016).

In this study, we present results on the effect of ions in

various atmospherically relevant mixtures of precursor va-

pors comprising sulfur dioxide (which is oxidized to sulfu-

ric acid), ammonia, monoterpenes (forming highly oxidized

molecules, HOMs; Ehn et al., 2014), NO

, and water, as

summarized in Table 1. Furthermore, we were able to de-

Table 1.

Overview of the four precursor vapor mixtures investigated

in the present study. The precursors were added to the chamber at

various atmospheric concentrations together with 40 ppbv (parts per

billion by volume) of ozone and ultrapure synthetic air (N

21) at 38 % relative humidity.

System no.

III

Monoterpenes (MTs)

XXXX

Sulfur dioxide (SO

)

XXX

Nitric oxide (NO)

XX

Ammonia (NH

)

X

termine the contribution of ion–ion recombination to ion-

induced new particle formation.

2 Methods

2.1 Experiment

The CLOUD chamber (Kirkby et al., 2011; Duplissy et al.,

2016) is an advanced facility to study nucleation pro-

cesses, with special emphasis on the control of ions. The

temperature-regulated stainless-steel cylinder of 3 m diam-

eter has a volume of 26.1 m

, which provides a wall loss rate

comparable to the condensation sink onto aerosol particles

in a pristine environment, and long dilution times (2–3 h, de-

pending on the flow drawn by the sampling instruments). To

ensure very low levels of contaminants, all inner surfaces are

electropolished and, prior to each experimental campaign,

the chamber undergoes a cleaning cycle of several days dur-

ing which it is first rinsed with ultrapure water and subse-

quently heated to 373 K while flushing at a high rate with hu-

midified ultrapure air containing several parts per million by

volume of ozone. Mass spectrometers confirm that the level

of contaminants is very low. Concentrations of sulfuric acid

and amines are below 10

−

. A sophisticated gas supply

system is used to control the trace gases added to the cham-

ber when experiments are conducted.

Ions are constantly produced in the chamber by galac-

tic cosmic radiation. Ion concentrations can be further in-

creased by using the CERN Proton Synchrotron (PS) pion

beam (3.5 GeV c

−

) as adjustable additional ionizing radia-

tion. Before the beam traverses the chamber, it is defocused

to a transverse size of about 1

5 m

5 m. Additional vari-

ation in ion concentrations is introduced when aerosol parti-

cles in the chamber grow to accumulation mode sizes and act

as a sink for small ions. Moreover, “GCR” ionization rates

vary at CLOUD, depending on whether the PS is operat-

ing or shut down (e.g., for maintenance) since muons from

the beam target are able to penetrate the beam stopper. The

GCR ionization rate is between 2 i.p. cm

−

(PS off) and

4 i.p. cm

−

(PS on). During our experiments the PS was

mostly operating; however, it was shut down throughout the

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Atmos. Chem. Phys., 17, 15181–15197, 2017

15184

R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

measurements for system IV. Ion-free conditions can be stud-

ied by using a high-voltage field cage (

30 kV, resulting in

20 kV m

−

) installed inside the chamber, which efficiently

scavenges ions when switched on (ion lifetime below 1 s).

2.2 Definitions

The particle nucleation rates reported in this study are de-

fined as follows (details of the calculation are provided in

Sect. 2.4). The total nucleation rate is

tot

iin

(1)

where

(“neutral”) is the nucleation rate in the absence of

any ions and

iin

is the ion-induced nucleation rate. Previ-

ous CLOUD studies (e.g., Kirkby et al., 2016) refer to

tot

gcr

depending on the ionization conditions (solely

by GCRs or enhanced with the CERN PS

beam, respec-

tively). When the nucleated particles are subsequently mea-

sured at a larger size, some of the initially charged particles

have been neutralized by ion–ion recombination; thus, the

particle formation rate at a specified detection threshold is

tot

rec

(2)

where

rec

is the formation rate of particles that were initially

charged, but neutral when detected (ion–ion recombination),

and

is the formation rate of particles, that were initially

charged and are still charged when detected. The ion-induced

formation rate at the specified detection threshold is

iin

rec

(3)

The neutral, i.e., non-ion-induced, particle formation rate at

the specified threshold is

but the

detected

total neutral par-

ticle formation rate is

n, tot

rec

(4)

Primary ions in the atmosphere are formed from the most

abundant constituents, N

and O

, which are then positively

and negatively charged, respectively. Collisions rapidly

transfer the positive charge to vapors with a high proton

affinity, such as H

or NH

, and the negative charge to

vapors with a high gas phase acidity, such as CO

−

, NO

−

or HSO

−

(Eisele, 1989; Ehn et al., 2011; Junninen et al.,

2010). The ions can attach further molecules such as water.

These so-called small ions are singly charged molecules or

molecular clusters in the electrical mobility range of 3.6–

0.6 cm

−

, corresponding to a mobility diameter of

0.75–1.79 nm. Here we refer to small ions as “cluster ions”,

and their concentration is provided in ion pairs per cubic cen-

timeter (i.p. cm

−

2.3 Instruments

A comprehensive set of instruments was used to charac-

terize the chemical and physical properties of the particles

and vapors in the CLOUD chamber. Cluster ions and newly

formed particles were monitored with ion and particle mo-

bility spectrometers and nanoparticle counters. The concen-

trations and number size distributions of ions were mea-

sured with a neutral cluster and air ion spectrometer (NAIS,

Airel Ltd.; Mirme and Mirme, 2013). The NAIS simultane-

ously measures the number size distribution of positive and

negative ions in the mobility diameter range of 0.75–45 nm

(Mirme and Mirme, 2013) by operating two cylindrical mo-

bility spectrometers in parallel. The sample flow enters the

analyzers close to the center electrode and naturally charged

ions are drifted towards the outer electrodes according to

their electrical mobility, transferring their charge onto one of

21 electrometer rings. Taking into account diffusional losses,

the spectra of electric currents can be inverted to number size

distributions of ions. After applying calibration corrections,

the ion concentrations are accurate to within 10 % (Wagner

et al., 2016). For operation at CLOUD, a dilution system was

employed to reduce the sample flow from the chamber. After

including the uncertainty on the dilution correction, the over-

all uncertainty in ion concentrations is 20 %. The NAIS is

equipped with sample preconditioning units (corona charg-

ers) that can charge the aerosol. In this way neutral aerosol

particles can also be measured, in the size range of 2–45 nm.

The NAIS periodically measures the offset currents of each

electrometer by charging the sample aerosol to the opposite

polarity of the subsequent analyzer and switching on an elec-

trical filter. By applying this procedure, no detectable aerosol

enters the spectrometers and possible offset currents can be

measured and the signals corrected (Manninen et al., 2016).

Particles were measured with two particle size magni-

fiers (PSMs, Airmodus Ltd.; Vanhanen et al., 2011) together

with condensation particle counters (CPCs; McMurry, 2000),

forming a pair of two-stage nanoparticle counters. The PSM

operates with diethylene glycol as the working fluid and

achieves supersaturated conditions by mixing heated satu-

rated air with the sample, and subsequently cooling the flow.

Since the saturation ratio can quickly be adjusted by altering

the flow of saturated air, the cutoff diameter (the diameter

with 50 % counting efficiency) of the PSM can be varied. In

this way, the PSMs were operated in a scanning mode that

spanned detection thresholds between approximately 1 and

3 nm. When operated in scanning mode, the number size dis-

tributions below 3 nm can be determined (Lehtipalo et al.,

2014; Kangasluoma et al., 2015). Particles that are activated

by the PSM are subsequently counted by a CPC. In this study,

we operated two PSMs in parallel: one of them measured all

particles, while for another, ions and charged particles were

removed from the sample flow with an ion filter. The ion filter

consists of two electrodes operated at 2.2 kV potential dif-

ference, generating an electric field that removes any ions

smaller than approximately 13 nm mobility diameter from

the sample flow. The inlet system is described in more de-

tail by Kangasluoma et al. (2016a). The two PSMs, without

and with an ion filter, measure the total particle concentration

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R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

15185

(PSMt) and the neutral (uncharged) component (PSMn), re-

spectively. The difference between the two PSMs gives the

charged fraction. From these particle concentrations (

tot

) we calculated the formation rates reported in this study.

When calculating formation rates, corrections are required

for coagulation losses to preexisting particles. These cor-

rections require knowledge of the particle size distributions,

which were measured with two aerosol mobility spectrom-

eters; a nano-SMPS (scanning mobility particle sizer, TSI

model 3938; Wang and Flagan, 1990) and a custom-built

SMPS. The TSI nano-SMPS was connected to a water CPC

(TSI model 3788) and measured the size distribution in the

range of 2–65 nm. The custom-built SMPS, consisting of

a TSI X-ray source as the neutralizer, a TSI-type long dif-

ferential mobility analyzer (DMA), and a CPC (TSI 3010),

measured the size distribution at 20–500 nm. The combina-

tion of these two instruments was used to calculate the full

size distribution.

The chemical composition of the gases was measured

with mass spectrometers and gas monitors. Concentrations

of monoterpenes (

-pinene,

-3-carene) were measured with

a proton transfer reaction time-of-flight mass spectrometer

(PTR-TOF-MS; model PTR3; Breitenlechner et al., 2017).

A new ionization chamber allows for 30-fold longer reac-

tion times and 40-fold higher pressure compared to previ-

ous PTR-MS instruments at comparable collision energy.

Coupled to the latest quadrupole-interfaced long-time-of-

flight mass analyzer (TOFWERK), sensitivities of up to

20 000 cps ppbv

−

at a mass resolution of 8000 m

/1m

are

achieved.

Sulfuric acid and organic HOMs were detected with

a chemical ionization atmospheric pressure interface time-of-

flight mass spectrometer (CI-APi-TOF; Jokinen et al., 2012).

In this instrument, neutral molecules and clusters are charged

by nitrate ions (NO

−

) formed by X-ray ionization of nitric

acid in a carrier flow of nitrogen. Nitrate ions then interact

with the sample air in an ion drift tube (chemical ionization).

After charging, the ions enter the atmospheric pressure in-

terface (APi), where they are focused while the pressure is

progressively reduced to 10

−

mbar. Subsequently the clus-

ters enter the time-of-flight mass spectrometer, where their

molecular composition is determined by precise mass mea-

surement. Concentrations are subject to a systematic scale

uncertainty, as well as uncertainties in charging efficiency

in the ion source, a mass-dependent transmission efficiency,

and sampling line losses (Kirkby et al., 2016). The estimated

error of absolute molecule concentrations is roughly a fac-

tor of 2.

Ammonia (NH

) concentrations were measured with

a quadrupole chemical ionization mass spectrometer (CIMS,

THS Instruments LLC). This instrument is equipped with an

APi unit (Eisele and Tanner, 1993). Primary ions are formed

by ionizing humidified synthetic air with a corona discharge,

producing

(

)

(Kürten et al., 2011). Neutral am-

monia molecules in the sample air interact with the ionized

water clusters forming

(

)

and are detected mainly

as NH

. The instrument was calibrated for the relevant range

of mixing ratios before and after the experiments by using

ammonia from a gas bottle diluted with nitrogen. The limit of

detection is approximately 20 pptv of NH

. The error of the

measurement was estimated as a factor of 2, which mainly

results from the use of different inlet systems during calibra-

tion and during operation at the CLOUD chamber.

Nitric oxide (NO) concentrations were determined with

a commercial NO monitor (ECO PHYSICS, model CLD

780 TR) using a chemiluminescence detector. With an in-

tegrating time of 60 s, the detection limit is 3 pptv. Nitrogen

dioxide (NO

) in the chamber was measured with a cavity-

attenuated phase shift nitrogen dioxide monitor (CAPS NO

Aerodyne Research Inc.). The baseline was monitored peri-

odically by flushing the instrument with synthetic air. Other

gas analyzers included the concentrations of sulfur dioxide

(SO

, Thermo Fisher Scientific, Inc., model 42i-TLE), ozone

, Thermo Environmental Instruments TEI 49C), and dew

point (EdgeTech).

2.4 Data analysis

We present a typical experiment sequence in Fig. 1. The ini-

tial conditions were neutral (high voltage (HV) at

30 kV)

and thus identical formation rates were measured at 1.5 nm

diameter from PSMn, with an electrostatic filter (green

curve), and PSMt, without an electrostatic filter (blue curve).

Measured ion pair concentrations during that phase of the ex-

periment are solely due to electrometer noise, which is scaled

up due to corrections for diffusional losses in the sampling

line and sample dilution (see Sect. 2.3 for details). When

the HV was switched off at 12:02 UTC, ions produced by

GCRs were no longer removed from the chamber and so the

concentration of cluster ions increased (Fig. 1c and d). This

resulted in an increased particle formation rate due to ion-

induced nucleation. As a result of ion–ion recombination,

some of the additional ion-induced particles were detected as

neutral particles (

rec

) and the remainder as charged particles

(

). In this way, we can measure all four components of the

total formation rate:

iin

rec

, and

. We calculated for-

mation rates at the mobility diameters of 1.5, 2.0, and 2.5 nm,

which correspond to mass diameters of about 1.2, 1.7, and

2.2 nm. The size of the smallest detected clusters is similar

to HOM di- or trimers, or eight sulfuric acid molecules.

Ion-induced nucleation may depend on numerous param-

eters, such as chamber temperature, concentration of cluster

ions, and concentration of precursors. In this study, we var-

ied these parameters in each studied chemical system to in-

vestigate their effect on ion-induced nucleation. A detailed

overview of the parameters and corresponding uncertainties

is provided in Table 2.

The formation rates (

, cm

−

) were calculated from

the time derivative of total particle concentration (

tot

) above

a specified threshold, corrected for the particle loss rates due

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15186

R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

Table 2.

Experimental ranges of temperatures (

), CERN proton synchrotron (PS) beam intensities, total ion pair production rates (IPRs),

and concentrations of cluster ions (mobility diameter 0.75–1.8 nm), monoterpenes (MTs), biogenic highly oxidized molecules (HOMs),

sulfuric acid (H

), nitric oxide (NO), nitrogen dioxide (NO

), and ammonia (NH

), and the corresponding uncertainties.

System I

System II

System III

System IV

Min

Max

Min

Max

Min

Max

Min

Max

Uncertainty

(

◦

)

−

25.2

25.5

−

25.2

25.5

5.0

5.3

5.2

25.4

0.1

PS beam intensity (Hz)

8.0E

5.1E

n/a

10 %

Total IPR (i.p. cm

−

)

4.4

54.9

4.4

35.7

4.4

1.8

20 %

[

Cluster ions

]

(i.p. cm

−

)

1.0E

5.8E

9.2E

5.6E

1.2E

2.9E

6.1E

1.2E

20 %

[

]

(pptv)

1956

1540

253

1578

134

1397

15 %

[

HOM

]

(cm

−

)

1.1E

3.8E

2.4E

6.2E

3.5E

1.8E

100 %

−

50 %

[

]

(cm

−

)

1.1E

1.0E

2.3E

1.6E

7.3E

100 %

−

50 %

[

]

(ppbv)

0.002

0.019

0.001

0.012

0.005

0.084

0.015

0.033

0.020

[

]

(ppbv)

n/a

0.038

13.499

0.052

2.065

0.200

[

]

(pptv)

n/a

178

1971

35 %

n/a: instrument was not installed for those experiments.

to dilution, wall losses, and coagulation with larger particles

(Kirkby et al., 2011; Almeida et al., 2013):

tot

dil

wall

coag

(5)

Since instruments continuously sample from the chamber,

a flow of synthetic air is needed to maintain constant pres-

sure. Therefore, the particle concentration in the chamber is

diluted at a rate given by

dil

tot

dil

(6)

with

dil

437

−

. Diffusional losses of molecules

and particles to the chamber walls (

wall

) were determined

empirically by observing the decay of sulfuric acid monomer

concentrations in the chamber after the photochemical pro-

duction of sulfuric acid was terminated by turning off the

UV lights. The wall loss rate is inversely proportional to the

mobility diameter of the particle and can therefore be scaled

to determine the wall loss rate for small clusters. Taking into

account the dependence on the square root of the diffusion

coefficient (Crump and Seinfeld, 1981) and its temperature

dependence (Hanson and Eisele, 2000), the wall loss rate can

be written as

wall

(

)

∑

′

max

′

(

′

)

wall

(

′

)

(7)

wall

(

′

)

116

−

(

ref

)

875

(

p, ref

′

)

(8)

where

is the mobility diameter threshold,

N(d

′

)

is the

concentration of particles with diameter

′

p, ref

82 nm

is the mobility diameter of the sulfuric acid monomer,

ref

278 K, and

is the chamber temperature. The total co-

agulation loss for particles larger than or equal to

p, k

(

coag

p, k

)

) was calculated from the measured number size

distribution of particles in the chamber (Seinfeld and Pan-

dis, 2016):

coag

(

)

p, max

∑

p, max

∑

i,j

(

)

(9)

with

i,j

5 if

i,j

1 if

midpoint di-

ameter for size bin with index

particle number con-

centration in bin

, and

(

)

coagulation sink for

particles of sizes

and

. The nucleation rate for each

experimental condition was obtained by calculating the mean

of the nucleation rates measured after reaching stable condi-

tions. To ensure a high-quality data set, we discarded results

for which the relative SD of the nucleation rate was larger

than 0.3. When studying the ratio of total to neutral nucle-

ation rates, we compared measurements from two PSMs. In

general, the agreement of the two instruments during neutral

conditions was very good. However, the few cases (

1 % of

all measurements) in which the formation rate of neutral par-

ticles (

n, tot

) exceeded the formation rate of total particles

(

tot

) by more than 30 % were excluded from the analysis.

This sometimes occurred due to measurement uncertainties

when nucleation rates were very low (

−

Uncertainties in the ratios of total to neutral nucleation

rates were calculated from the uncertainties of the concen-

tration measurements, as well as the sink terms. Beyond that,

there are a few more limitations to our method.

One source of uncertainty is the composition dependency

of the detection thresholds of the PSMs. The instruments

were calibrated using tungsten oxide particles before the

measurement campaign. However, a higher detection thresh-

old has been reported for organic particles (Kangasluoma

et al., 2014). To account for this we compared the cutoff

diameters of the PSM to the size bins of the NAIS in each

chemical system used here and chose the diameters based on

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R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

15187

n,tot

rec

tot

iin

Total

Neutral

Negative

Positive

Figure 1.

Example of an experimental run to illustrate individual

particle formation rates, measured at the 1.5 nm detection thresh-

old.

(a, b)

Particle formation rates measured using the PSMt (with-

out ion filter, blue curve) and PSMn (with ion filter, green curve);

(c, d)

cluster ion concentrations (

0.75–1.8 nm) measured with the

NAIS. Prior to 12:02 UTC the high-voltage (HV) clearing field was

on to establish ion-free conditions in the chamber and thus PSMt

and PSMn measured the same formation rates (

). After switching

off the HV, the ions produced by galactic cosmic rays (GCRs) were

no longer removed from the chamber

(d)

and the particle formation

rates increased

(b)

. The increase in particle formation rate measured

with the PSMt provides the ion-induced formation rate (

iin

), and

the increase in particle formation rate measured using the PSMn

provides the fraction of

iin

that is detected as neutral particles due

to ion–ion recombination. The difference of PSMt and PSMn sig-

nals provides the fraction of

iin

detected as charged particles. The

run conditions are

◦

[

270 pptv,

[

40 ppbv,

[

−

, and

[

084 ppbv (system III).

this comparison. The NAIS is insensitive to composition as it

detects the size based on ion mobility, and the size accuracy

has been verified in laboratory calibrations (Wagner et al.,

2016). The remaining uncertainty is of the order of

2 nm

based on limited size bin resolution and run-to-run variabil-

ity.

When comparing the PSMt and PSMn measurements,

a charge effect on the instruments’ detection efficiency might

further affect our results. Ions are known to activate at lower

supersaturations compared with neutral particles (Winkler

et al., 2008). For the PSM, the cutoff diameter for ions can

be up to 0.5 nm smaller than for neutral particles, depend-

ing on particle composition (Kangasluoma et al., 2016b). In

practice, the detected ions could be a bit smaller than the

neutral particles at the same saturation ratio. As a result, de-

pending on the particle growth rate, the ratio

tot

would

be slightly increased (the ratio

n, tot

tot

slightly decreased).

Although we do not expect this charge effect to be significant

in our study, we want to point out that the reported charged

fractions represent upper-limit estimates.

Further quantification of the effect of charge and com-

position on the detection threshold would require extensive

knowledge of the particle and cluster composition and their

activation properties in each system and is left for future stud-

ies.

3 Results

3.1 Fraction of neutral particle formation in different

chemical systems

We will use the term “neutral fraction” at a given detection

threshold to indicate the measured ratio of the neutral to to-

tal formation rates,

n, tot

tot

. Figure 2 illustrates the neutral

fraction of all four systems combined, at several detection

size thresholds. A progressive neutralization of the clusters

can be seen as the particles grow in size; the median neu-

tral fractions are 0.50, 0.68, and 0.94 at thresholds of 1.5,

2.0, and 2.5 nm, respectively. While an exponential decrease

in the charged fraction was reported in an earlier study (Yu

and Turco, 2011), we observed a linear decay. However, the

charging state is sensitive to the age of the sample, which

may be different in our study (characteristic mixing time; see

Sect. 3.2) compared to the data analyzed by Yu and Turco

(2011).

The first chemical system we studied (system I) contained

biogenic vapors alone. Monoterpenes (MTs;

-pinene,

-3-

carene, or a mixture, C

) injected into the chamber were

subsequently oxidized by ozone and hydroxyl radical (OH),

forming HOMs. We found that the importance of charge de-

creased towards high MT concentrations (Fig. 3a). Although

we study the neutral fraction here, which includes neutral

nucleation and recombination of ion-induced particles, the

observed behavior indicates that ion-induced nucleation also

follows this pattern. This was previously reported by Kirkby

et al. (2016), as a result of

iin

saturating at the GCR ion

production rate limit. At low temperatures, all HOM species

have reduced volatility and thus a larger fraction can par-

ticipate in particle nucleation and growth – although this is

partially compensated for by the slower production rate of

HOMs. Temperature also affects the composition and stabil-

ity of formed HOM clusters (Frege et al., 2017). As a result,

the neutral fraction at a given MT concentration is higher at

lower temperatures (Fig. 3a and b). Compared to 1.5 nm, par-

ticles reaching 2.0 nm in diameter had more time to become

neutralized by ion–ion recombination and were already more

stable; thus, the charge was less important to stabilize them

(Fig. 3b). Particles measured at the 2.5 nm detection thresh-

old were mostly neutral at all studied conditions (Fig. 3c).

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R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

-2

-1

n,tot

/ J

tot

(a) d

> 1.5 nm

Median: 0.50

[Cluster ions] (i.p. cm

-3

)

(b) d

> 2.0 nm

Median: 0.68

> 2.5 nm

Median: 0.94

Figure 2.

The neutral fraction of particle formation rates measured at detection thresholds of

(a)

1.5 nm,

(b)

2.0 nm, and

(c)

2.5 nm vs. cluster

ion concentrations. All four systems are included. Each red dot indicates the median neutral fraction and ion pair concentration. Whereas

ion-induced nucleation can result in large charged fractions at the smallest detection threshold, 1.5 nm

(a)

, more than 90 % of particles are

neutral once they reach 2.5 nm

(c)

-2

-1

n,tot

/ J

tot

(a) d

> 1.5 nm

[MT] (pptv)

(b) d

> 2.0 nm

> 2.5 nm

-25

Chamber temperature (°C)

Figure 3.

The neutral fraction of particle formation rates vs. monoterpene (MT) concentration for pure biogenic conditions (system I) at

detection thresholds of

(a)

1.5 nm,

(b)

2.0 nm, and

(c)

2.5 nm. The color scale indicates chamber temperature (

−

25, 5, 25

◦

C).

With the addition of sulfur dioxide (system II) the in-

fluence of charge depended on the concentrations of both

monoterpenes and sulfuric acid. We therefore studied the

neutral fraction as a function of the product of the concen-

trations of monoterpenes and sulfuric acid (Fig. 4) since

only then the trends became clearly visible. The observed

decrease in the charged fraction at the lowest temperature

(Fig. 4a, compared to Fig. 3a) suggests higher cluster sta-

bility when sulfuric acid is present. Otherwise, we observed

trends similar to system I. Once again, particles measured

at the 2.5 nm detection threshold were mostly neutral at all

studied conditions (Fig. 4c).

After addition of NO (system III) to study the possible

effect of NO

on new particle formation, the gas mixture

comprised monoterpenes, sulfuric acid, and nitrogen oxides

(NO and NO

). NO

are found to decrease the particle for-

mation rates from monoterpene oxidation in previous stud-

ies (Wildt et al., 2014). Here, we found a decreasing neutral

fraction with increasing concentrations of NO and of clus-

ter ions. We therefore show in Fig. 5 the neutral fraction vs.

[

]·[

]

[

]·[

cluster ions

]

)

. The neutral fraction

decreased towards lower values of this quantity (Fig. 5a).

For this system, the nucleation rate is primarily driven by

HOMs rather than sulfuric acid; thus, a repeated pattern can

be seen at various [H

] levels in Fig. 5a. However, sulfu-

ric acid adds to the stability of 2.0 nm particles, as the neutral

fraction is lowest with [H

] below the detection limit of

−

. As before, particles measured at the 2.5 nm detec-

tion threshold were mostly neutral at all studied conditions

(Fig. 5c).

With the addition of ammonia we aimed to reproduce

an environment similar to the boreal forest at the station

for measuring ecosystem–atmosphere relations (SMEAR

II; Hari and Kulmala, 2005) in Hyytiälä, southern Fin-

land, involving a mixture of monoterpenes, sulfuric acid,

nitrogen oxides, and ammonia (system IV). During new

particle formation events, typical conditions in Hyytiälä

are [cluster ions]

440–580 i.p. cm

−

[

30–140 pptv,

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-2

-1

n,tot

/ J

tot

(a) d

> 1.5 nm

[MT]*[H

] (pptv cm

-3

)

(b) d

> 2.0 nm

> 2.5 nm

-25

Chamber temperature (°C)

Figure 4.

The neutral fraction of particle formation rates vs. the product of the monoterpene and sulfuric acid concentrations (system II), at

detection thresholds of

(a)

1.5 nm,

(b)

2.0 nm, and

(c)

2.5 nm.

-2

-1

n,tot

/ J

tot

(a) d

> 1.5 nm

([MT]*[H

]) / ([NO]*[Cluster ions])

(b) d

> 2.0 nm

> 2.5 nm

(cm

-3

)

Figure 5.

The neutral fraction of particle formation rates vs. the product of the concentrations of monoterpenes (MTs) and sulfuric acid

) divided by the concentration of nitric oxide (NO) and cluster ions (system III), at 5

◦

C temperature and detection thresholds of

(a)

1.5 nm,

(b)

2.0 nm, and

(c)

2.5 nm.

[

4–8

−

[

20–90 pptv,

[

260–1130 pptv,

[

50–210 pptv, and

3–14

◦

The values in the ranges correspond to the 25th and 75th

percentiles. The dependency of the neutral fraction on the

different variables in this system seemed to be similar

to system III, although the neutral fractions, especially at

1.5 nm, were clearly higher. The neutral fraction of parti-

cle formation rates at 1.5 nm ranged from about 10 % at

the low MT and H

concentrations up to 80–90 % at

the high concentrations (Fig. 6a). The latter corresponded to

≈

◦

[

]≈

690 pptv,

[

]≈

−

, NH

≈

180 pptv,

[

]≈

20 pptv, and [cluster ions]

≈

600 i.p. cm

−

and, under these conditions,

exceeds the ion production

rate limit for

iin

. In this multicomponent system, ammo-

nia helps to stabilize the sulfuric acid and thus the neutral

fraction of particle formation at 1.5 nm and 5

◦

C (Fig. 6a)

is larger towards lower MT and H

concentrations than

seen in Fig. 5a (for H

−

). We speculate

that this is due to a similar base-stabilization mechanism, as

observed in Kirkby et al. (2011) for a ternary sulfuric acid–

water–ammonia system, although the multicomponent sys-

tem studied here is more complicated than pure acid–base

systems. Ions are still important in stabilizing the particles at

warmer temperatures (Fig. 6a, 25

◦

C). As for all other sys-

tems, particles measured at the 2.5 nm detection threshold

were mostly neutral at all studied conditions (Fig. 6c).

We display a comparison of the neutral fractions of particle

formation rates at 5

◦

C for all four systems in Fig. 7. Exam-

ining the smallest studied clusters (1.5 nm, Fig. 7a) demon-

strates the significance of ions for all systems, and also that

ammonia helps stabilize the clusters, reducing the impor-

tance of the charge. As the particles grow, charged particles

are gradually neutralized by ion–ion recombination (Fig. 7b)

until reaching 2.5 nm, at which less than 10 % of all parti-

cles carry a charge (Fig. 7c). Values larger than 1 result from

nucleation rates close to the detection limit (approximately

−

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R. Wagner et al.: The role of ions in new particle formation in the CLOUD chamber

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n,tot

/ J

tot

(a) d

> 1.5 nm

([MT]*[H

]) / ([NO]*[Cluster ions])

(b) d

> 2.0 nm

> 2.5 nm

Chamber temperature (°C)

Figure 6.

The neutral fraction of particle formation rates vs. the product of the concentrations of sulfuric acid and monoterpenes divided by

the concentrations of nitrogen oxide (NO) and cluster ions, after adding ammonia (NH

) to the chamber (Hyytiälä simulation, system IV),

at detection thresholds of

(a)

1.5 nm,

(b)

2.0 nm, and

(c)

2.5 nm.

III

0.25

0.5

0.75

1.25

1.5

n,tot

/ J

tot

(a) d

> 1.5 nm

III

System

(b) d

> 2.0 nm

III

> 2.5 nm

Figure 7.

Comparison of the neutral fraction of particle formation rates for all four chemical systems at 5

◦

C and detection thresholds of

(a)

1.5 nm,

(b)

2.0 nm, and

(c)

2.5 nm. The box and whisker plots show the median (red line), upper, and lower quartiles (rectangular box) and

upper and lower ranges (error bars). Red crosses indicate outliers.

3.2 Comparison of CLOUD measurements to

atmospheric observations at SMEAR II, Hyytiälä,

Finland

In Figs. 8 and 9, we compare the CLOUD nucleation and

formation rates with those reported from several atmospheric

studies conducted in Hyytiälä. We compared the 1.5 nm for-

mation rates in CLOUD with the nucleation rates of 1.5 nm

particles (Kulmala et al., 2013) and the recombination rates

of 1.5–1.7 nm particles (Kontkanen et al., 2013). In addi-

tion, we compared the formation rates of 2.0 nm particles

in CLOUD with the formation rates at 2 nm from Manni-

nen et al. (2009). Most of the Hyytiälä measurements were

carried out in spring, when the temperatures ranged between

around

−

5 and 15

◦

C (median 6.3

◦

C).

In Fig. 8, we compare CLOUD (system IV) and Hyytiälä

measurements of the neutral and ion-induced nucleation

rates vs. cluster ion concentrations. At CLOUD, the frac-

tions of pure neutral and ion-induced particle formation do

not depend on the particle detection threshold. That means

that, although the total particle formation rate decreases

with increasing detection threshold diameter, the relative

contribution of ion-induced nucleation remains the same.

The

iin

tot

fraction increases with cluster ion concen-

tration from about 25 % at the lowest ion concentrations,

580 i.p. cm

−

, to more than 90 % at 1230 i.p. cm

−

(Fig. 8d).

The ion-induced fraction in Hyytiälä at 1.5 nm (triangle,

Fig. 8d) is almost 1 order of magnitude below the values

at CLOUD, but the cluster ion concentration is also respec-

tively lower than that in CLOUD. From Fig. 6 it is clear that

the neutral and ion-induced fractions depend on the cluster

ion concentration in this chemical system. The difference is

smaller at the 2.0 nm detection threshold; however, the atmo-

spheric values are still roughly a factor of 2 lower than at

CLOUD (triangle and diamond, Fig. 8e).

For comparison, in Fig. 9 we display the measured recom-

bination and charged fractions of the particle formation rates

vs. cluster ion concentrations for CLOUD (system IV) and

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15191

-2

-1

/ J

tot

> 1.5 nm

(a)

> 2.0 nm

(b)

> 2.5 nm

(c)

-6

-4

-2

CS (s

-1

)

-2

-1

iin

/ J

tot

(d)

[Cluster ions] (i.p. cm

-3

)

(e)

Kulmala et al., Kontkanen et al. (2013)

Manninen et al. (2009)

(f)

Figure 8.

Comparison of CLOUD (system IV, circles) and Hyytiälä, Finland (triangles and diamonds), measurements of the neutral and

ion-induced fractions of particle nucleation rates vs. cluster ion concentrations at 5 and 25

◦

C and detection thresholds of

(a, d)

1.5 nm,

(b, e)

2.0 nm, and

(c, f)

2.5 nm. The color scale indicates the condensation sink (CS) onto aerosol particles (wall loss and dilution loss not

included). The condensation sink in Hyytiälä is on average 2

−

(Nieminen et al., 2014).

-2

-1

rec

/ J

tot

> 1.5 nm

(a)

> 2.0 nm

(b)

Kulmala et al., Kontkanen et al. (2013)

Manninen et al. (2009)

> 2.5 nm

(c)

-8

-6

-4

-2

CS (s

-1

)

-2

-1

'

/ J

tot

(d)

[Cluster ions] (i.p. cm

-3

)

(e)

(f)

Figure 9.

Comparison of CLOUD (system IV, circles) and Hyytiälä, Finland (triangles and diamonds), measurements of the charged and

recombination fractions of particle formation rates vs. cluster ion concentrations at 5

◦

C and detection thresholds of

(a, d)

1.5 nm,

(b,

2.0 nm, and

(c, f)

2.5 nm. The color scale indicates the condensation sink (CS) onto aerosol particles (wall loss and dilution loss not

included). The condensation sink in Hyytiälä is on average 2

−

(Nieminen et al., 2014).

Hyytiälä. Comparison of ion-induced and charged fractions

at CLOUD at the 1.5 nm threshold (Figs. 8d and 9d) show

that a fraction of the ion-induced particles has already been

neutralized by ion–ion recombination, even at the 1.5 nm de-

tection threshold. This results since the mean age of the par-

ticles sampled by the PSMn or PSMt at any instant in time

includes the characteristic mixing time in the CLOUD cham-

ber, which is several minutes and comparable to the ion–

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