An air-to-air ultrafine particle concentrator (Aerosol Dynamics Inc.
concentrator; ADIc) has been designed to enhance online chemical
characterization of ambient aerosols using aerosol mass spectrometry. The ADIc
employs a three-stage, moderated water-based condensation growth tube
coupled to an aerodynamic focusing nozzle to concentrate fine particles into
a portion of the flow. The system can be configured to sample between
1.0 and 1.7 L min
Particles in the ambient atmosphere are of concern for human health, air
quality and climate change (Pope and Dockery, 2006; Lelieveld et al., 2015;
IPCC, 2014). Measurement of the chemical characteristics of particles, and
the health effects associated with their inhalation, often benefits from
higher sample load, which can be achieved by increasing sample flow rate,
extending sampling time or using a particle concentrator. Enrichment of
particle number or mass concentration is particularly important for
measurements in regions where particle concentrations are low, such as in
Arctic or Antarctic background areas (10–1000 particles cm
Several air-to-air concentrators have been designed to increase the
concentration of particles with respect to the suspending gas volume and to
thereby provide enhanced aerosol detection. To be beneficial, the
concentrator should be small, easy to maintain and capable of operating
several days or even weeks unattended. Even more importantly, the
concentrator should provide stable enrichment of particles and maintain
aerosol chemical and physical and properties such as composition and size
distribution. Virtual impactors are a well-known type of air-to-air particle
concentrators that use a low-velocity sampling probe to sample a particle
flow exiting from a nozzle, but they are typically ineffective for the
submicrometer (< 1
Here we present a new air-to-air particle concentrator, the Aerosol Dynamics
Inc. concentrator (ADIc), that is based on the three-stage, laminar-flow,
water-based condensational growth approach used in the Sequential Spot
Sampler (Eiguren Fernandez et al., 2014; Pan et al., 2016) and in some
water condensation particle counters (CPCs; Hering et al., 2017, 2018). This
system is designed specifically for instruments with low sampling flow rates
on the order of 0.1 L min
The three-stage growth column version of the ADIc described here eliminates excess water vapor in the output flow and decreases the residence time for the particle in the droplet phase, with the objective of minimizing chemical artifacts as well as providing long-term stability. The ADIc is a smaller-scale version of the approach used in the nanoparticle charger reported by Kreisberg et al. (2018), for which chemical artifacts, evaluated using thermal desorption chemical ionization mass spectrometry, were found to be mostly insignificant. The ADIc is tailored for use with an aerosol mass spectrometer, such as the Aerodyne Aerosol Mass Spectrometer (AMS), the Aerodyne Aerosol Chemical Speciation Monitor (ACSM) or the ATOFMS. In this paper, the ADIc was evaluated in laboratory experiments that explored its influence on particle size and chemical composition. The ADIc was also evaluated in field measurements conducted in two different environments (urban background and suburban) and with different commonly used types of aerosol mass spectrometers. Moreover, long-term (weeks to months) unattended operation of the ADIc was demonstrated.
The ADIc uses a laminar flow, water-based condensation growth tube coupled
to an aerodynamic focusing nozzle to provide concentration of particles from
a 1–1.7 L min
Schematic of the Aerosol Dynamics Inc. concentrator (ADIc) with enlargement of the focusing nozzle.
Within the growth tube, particles with diameters above 5–10 nm are
activated and grow by condensation to form droplets of approximately 1.5–4
The exact design of the focusing and flow extraction nozzle is based on
numerical modeling done using the Comsol Multiphysics package. Numerical
modeling results, presented in Fig. S1 in the Supplement for the final design, show that
particles smaller than 1
Two prototype concentrators (Prototype 1 and 2) were used in this study,
both having the same dimensions for the growth tube and nozzle. The
conditioner, initiator and moderator are 140, 51 and 102 mm long,
respectively, separated by 7.5 mm thick insulator sections. In both
prototypes the growth tube was lined with a 9 mm ID,
The conditioner and moderator were cooled using Peltier heat pumps, and the
initiator and focusing nozzle were heated resistively. All three regions
used proportional–integral–derivative (PID) control to maintain set-point
temperatures. Distilled water was injected into the initiator stage at a
rate of 5
The performance of the ADIc for particle counting was evaluated in the
laboratory at Aerosol Dynamics Inc. (ADI) using monodisperse particles
generated by atomization, followed by drying and charge conditioning (soft
X-ray, Model 3087, TSI Inc., Shoreview, US). Particles were size-selected
using a nano-differential mobility analyzer (DMA; Model 3085, TSI Inc.,
Shoreview, US) for sizes between 5 and 60 nm and using the Aerosol
Dynamics Inc. high-flow DMA (Stolzenburg et al., 1998) for sizes between 20
and 400 nm. Particle concentrations were measured in the sample flow and
in the concentrated output flow using water-based CPCs. Prototype 1 was
evaluated with mono-mobility ammonium sulfate (AS) particles with a pair of
prototype Model 3785 (TSI Inc., Shoreview, US) water-based CPCs and a Model
3783 CPC (TSI Inc., Shoreview, US) to simultaneously measure particle
concentrations in the sample flow, in the discard flow and in the
concentrated output flow, respectively. The sample flow was fixed at 1.0 L min
Approximate temperature and flow settings for the ADIc
experiments presented in this study. ADI represents Aerosol Dynamics Inc., ARI Aerodyne Research, Inc. and FMI the Finnish Meteorological Institute.
Similar evaluation experiments were carried out on Prototype 2, but its
operation was tested under two flow regimes. First, experiments were done at
1.0 L min
In addition to laboratory-generated AS particles, both prototypes were tested with laboratory air using a pair of water-based CPCs, one sampling upstream of the ADIc and one sampling downstream.
The performance of the ADIc in terms of particle chemistry was evaluated at Aerodyne Research, Inc. (ARI) and at the Finnish Meteorological Institute (FMI). Laboratory experiments were carried out using particles generated with a constant output atomizer (Model 3076, TSI Inc., Shoreview, US) from AS or ammonium nitrate (AN) in deionized water or from dioctyl sebacate (DOS) in 2-propanol. Generated particles were dried with a silica gel dryer, and the desired monodisperse particle size fraction was selected using a DMA (Model 3080, TSI Inc., Shoreview, US). A valve system was used to alternate between passing the particles through the ADIc and bypassing it. Temperature and flow settings used in the ADIc during the ARI and FMI experiments are given in Table 1.
Particle size and chemical composition were measured with several different
versions of the AMS, including a high-resolution time-of-flight aerosol mass
spectrometer (HR-AMS; Aerodyne Research Inc., Billerica, US; DeCarlo et al.,
2006), a soot-particle aerosol mass spectrometer (SP-AMS; Aerodyne Research
Inc., Billerica, US; Onasch et al., 2012), a quadrupole aerosol mass
spectrometer (Q-AMS; Aerodyne Research Inc., Billerica, US; Canagaratna et
al., 2007) and a quadrupole aerosol chemical speciation monitor (ACSM;
Aerodyne Research Inc., Billerica, US; Ng et al., 2011). These instruments
all operate on the same principle. Aerosol particles are sampled through an
aerodynamic lens, forming a narrow particle beam that is transmitted into
the detection chamber where the non-refractory species are flash-vaporized
upon impact on a hot surface (600
HR- and SP-AMS data were analyzed with the Squirrel (v1.57H)/Pika (v1.16H) and Squirrel (v1.60P)/Pika (v1.20P) analysis package, respectively. Additionally, high-resolution (HR) size distribution data from the SP-AMS were analyzed with the Squirrel (v1.62A)/Pika (v1.22A) package. Both the HR-AMS and SP-AMS instruments were equipped with a multiple slit chopper (efficient Particle Time-of-Flight, ePToF, chopper) with 50 % particle throughput. The measured size distributions were normalized to the mass concentrations measured in the mass spectrum mode. Q-AMS data were analyzed with AMS Analysis Toolkit 1.43. ACSM data were analyzed with ACSM Local (v1.6.1.1). All of the analysis software runs in the Igor 6 (WaveMetrics, Inc.) programming environment. The three AMS instruments and the ACSM were calibrated for ionization efficiency (IE) of nitrate and relative ionization efficiency (RIE) of both ammonium and sulfate, using size-selected single-component particles of AN or AS (Budisulistiorini et al., 2014).
The ADIc was tested for ambient aerosol at two different locations. At ARI,
particles were sampled from a rooftop sampling station on the ARI building
at 45 Manning St., Billerica, MA (42.53,
The second ambient sampling location was at an urban background station
(SMEAR III; Station for Measuring Ecosystem-Atmosphere Relationships, 60.20,
24.95; 30 m a.s.l., described by Järvi et al., 2009) located at the
Kumpula campus near the FMI building, about 5 km NE of the city
center of Helsinki, Finland. The station is surrounded by office buildings on one side
and a small forest and botanical garden on the other side. Ambient particles
were sampled through a 2.5
Figure 2 shows laboratory results for monodisperse AS particles for two flow
regimes. The measured concentration factor, defined as the ratio of particle
number concentration in the output flow of the ADIc to that in the sample
flow, is plotted as a function of particle mobility diameter. Data for the
lower flow regime are from Prototype 1, which was subsequently tested at ARI
for aerosol chemical species. For the lower flow, the average measured CF
was
Size-dependent concentration factor for the ADIc for higher (triangles) and lower (circles) flow regimes as a function of particle size. The red line indicates the average of the higher flow data. The blue line is a guide for the eye. Data are from two different prototype instruments, as indicated.
The ratio of measured / theoretical CF was
Measured and theoretical concentration factors (CFs) for ammonium nitrate (AN) and ammonium sulfate (AS) obtained in the laboratory tests.
To evaluate the stability of the ADIc, both prototypes were operated for
several days while sampling laboratory air. Particle number concentrations
were measured in the sample flow and in the output flow. Particle
concentration varied between 900 and 15 000 particles cm
The dependence of the CF on particle chemical composition was evaluated in the laboratory with size-selected 300 nm AS and AN particles, sampling with the Q-AMS with and without the ADIc in front. The theoretical and the measured CF for ammonium and sulfate from AS and for ammonium and nitrate from AN are given in Table 2. Compared to the CF obtained for particle number concentration, the ratio of measured / theoretical CF was the same for AS, while for AN the measured CF was slightly closer to the theoretical CF.
The influence of the ADIc on particle size was investigated by using
monodisperse AS, AN and DOS particles in the size range of 30 to 340 nm
(mobility diameter). Size and chemical composition of particles with and
without the ADIc were analyzed by an SP-AMS. Measurements were carried out
in the high-flow regime (theoretical CF of 21.3). Figure 3 shows the vacuum
aerodynamic diameter (
Particle size measured with an SP-AMS for 70–700 nm particles (vacuum aerodynamic diameter) of sulfate, nitrate and organics (from DOS) with and without concentration by the ADIc. Corresponding mobility diameters were 30–340 nm.
The performance of the ADIc for ambient aerosol was examined at two
locations: at a rooftop sampling station on the ARI building and at SMEAR
III in Helsinki. In order to investigate the impact of the ADIc on aerosol
organic and rBC chemistry, the SP-AMS was installed behind the ADIc at SMEAR
III and alternated every 30 min between measuring the output flow of the
ADIc and a bypass line. Measurements were performed on 11 different days in
June, July and August 2018, with a total sampling time of
The correlations between the mass spectral ions with and without the ADIc for
each fragment family are presented in Fig. 4c–f. The correlation was
uniformly high (
Mass spectra for ambient organics and rBC measured with
and without ADIc (
Overall, based on these tests, it can be concluded that passing through the ADIc does not significantly change the fragmentation or the elemental composition of organics or rBC in the ambient particles. However, due to the larger CF for rBC than for organics, the mass fraction of rBC in ambient particles increased slightly with the ADIc (Fig. S4).
The SP-AMS data with and without the ADIc were also used to investigate the impact of the ADIc on particle mass size distributions. Figure 5 compares the mass size distribution for organics, sulfate, nitrate and ammonium sampling through the ADIc and sampling from the bypass line. The PToF data were collected and analyzed in unit mass resolution (UMR) mode. Figure 5 demonstrates that the size distribution of ambient aerosol particles was not affected by passing through the ADIc. In addition, Fig. 5d shows significant improvement in the signal-to-noise ratio for ammonium when concentrating the sample flow.
Mass size distributions measured without (left axis) and
with (right axis) the ADIc for organics
Additional SP-AMS size distribution data were collected and analyzed in HR
mode on one day, with a total sampling time of 70 min in bypass and 70 min through the ADIc. HR size distributions are shown in Fig. 6 for
major chemical species and for several specific fragment ions. The much
higher signal-to-noise ratio in the concentrated PToF traces gives better chemical
resolution of the size distribution. The bimodal size distribution for
organics is clear in the ADIc data in Fig. 6a, with hydrocarbon-like
fragments (e.g.,
Mass size distributions measured without (left axis) and
with the ADIc (right axis) for organics
The long-term operation of the ADIc was tested at ARI where it ran for more
than 3 weeks without user maintenance or intervention. The measured CFs
from comparing the Q-AMS mass loading to the HR-AMS mass loading are
presented in Fig. 7. Average values of CF are presented in Table 3, along
with the ratio of the mass loadings during bypass periods. The theoretical
CF was calculated from the ADIc discard flow rate and the Q-AMS inlet flow
rate (equal to ADIc outlet flow) as the theoretical CF
Measured and theoretical concentration factors in ambient
measurements at ARI. The measured CF was calculated from the ratio of
Q-AMS
The measured CFs for nitrate and sulfate were 85 % to 90 % of theoretical
CFs, consistent with the laboratory measurements presented in Table 2. The
agreement between the two instruments during bypass periods was excellent
for nitrate and sulfate (Table 3). The measured CF for ammonium was higher
than the theoretical value, which may indicate that the aqueous droplets in
the ADIc initiator and moderator stages absorbed gas-phase ammonia that
remained in the particles after drying. This effect has been observed for
acidic particles in the miniature VACES (Saarikoski et al., 2014). The
ambient aerosol in this study was possibly slightly acidic, with an average
ratio of measured to predicted ammonia of
Ambient measurements at ARI showing ambient relative
humidity
The measured concentration factor (
Ambient measurements at SMEAR III showing the mass
loadings for organics
The performance of the ADIc with ambient aerosol was also tested
systematically under two flow regimes. Although the growth tube in the ADIc
is sized for low-flow operation, in some cases it can be beneficial to
operate the ADIc with the largest possible CF, for example, when very small
signals (e.g,. metals, PToF) are of interest or the ambient concentrations
are extremely low. High (1.7 L min
The time series of all chemical species measured with the ACSM
Time series of ammonium and
The relative humidity was measured with the ADIc near the Q-ACSM inlet. RH
was relatively constant at
In terms of Q-ACSM measurement, a particularly important improvement in
the signal-to-noise ratio was achieved with the ADIc. Fig. 9a and b show 30 min
time resolution data collected with the Q-ACSM without the ADIc, and Fig. 9b and d display 10 min time resolution data collected with the
Q-ACSM
The ADIc is tailored for the low (
Particle chemical composition and particle size measured with an SP-AMS were not affected by the condensational growth and evaporation process in the ADIc. Moreover, the ADIc ran unattended for a period of almost 1 month at a field site. Measured concentration factors for ambient aerosol particles in two different locations showed some variation that is not fully understood. However, the ADIc provides improved detection of low signals that outweighs a slight increase in uncertainty in the mass loadings. Improved detection limits will be important, especially in remote areas where particle concentrations are low and for measuring size distributions that typically need longer averaging periods. Additionally, use of the ADIc will be important for improving source apportionment with Q-ACSM data by gaining better time resolution and/or signal-to-noise ratio.
Data presented in this article are available upon request.
The supplement related to this article is available online at:
SS, HT, SVH, AEF and LRW designed the experiments. MA, KT, LRW, PC, TH, AEF, SRS and GSL conducted measurements in laboratory and field. Data analysis and interpretation of the measurement data was done by SS, LRW, AEF and SVH. Working environment and financial support was provided by HT at FMI, JTJ and DRW at Aerodyne and SVH at Aerosol Dynamics. SS, LRW and SVH prepared the manuscript with contributions from all co-authors.
Aerosol Dynamics Inc. holds a patent on the particle focusing technology.
Funding is gratefully acknowledged from the US Department of Energy, Small Business Research Program (grant no. DESC0004698), the Cityzer (Business Finland project Dnro:3021/31/2015), TAQIITA (Business Finland project Dnro:2634/31/2015) and the Launching Regional Innovations and Experimentations Funds (AIKO), governed by the Helsinki Regional Council (project HAQT, AIKO014).
This research has been supported by the US Department of Energy (grant no. DESC0004698), Business Finland (grant nos. 3021/31/2015 and 2634/31/2015) and AIKO (grant no. AIKO014).
This paper was edited by Charles Brock and reviewed by two anonymous referees.