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A New Methodology for Continuous Scanning of Particle Aerodynamic Diameter and Application to Filtration Performance Assessment of a Room Air Purifier

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Abstract and Figures

*** Note: the accompanying slideshow is accessed via the "Linked Data" tab below *** The Aerodynamic Aerosol Classifier (AAC) is a novel instrument that classifies particles based on their aerodynamic diameter. This is accomplished by passing the aerosol between spinning concentric cylinders with a coaxial sheath flow. Particles that have aerodynamic diameters larger than the AAC setpoint are dominated by the centrifugal force and impact the outer cylinder surface, while smaller particles remain entrained in the sheath flow; only particles with a narrow range of aerodynamic diameters pass through the AAC classifier. Particle sizes between 25 nm and 6.7 microns can be selected independent of the aerosol charge state, with a high transmission efficiency limited only by diffusion and impaction losses. This technique can be used to measure an aerosol's aerodynamic size distribution by stepping the AAC setpoint while recording the classified particle number concentration. This stepping procedure requires long measurement times to achieve reasonable spectral resolutions. To overcome this limitation, a scanning AAC inversion was developed. Following a similar methodology as the Scanning Mobility Particle Sizer (SMPS) inversion, this new approach allows the aerodynamic size distribution to be continuously measured by varying the classifier speed while measuring the classified particle concentration. By exponentially ramping the classifier speed, the change in the centrifugal force a particle experiences during its classifier residence time is independent of its inlet time. Furthermore, when the scan time is sufficiently longer than the scan speed ramping constant, the scanning AAC transfer function converges to the same shape as the steady state transfer function. This new methodology is called the "Scanning Aerodynamic Size Spectrometer" (SASS). Application of the SASS is demonstrated by collecting accelerated measurements of the ambient air particle size distributions in a room before, during and after operation of a commercial room air purifier. Additionally, a filter sample was taken from the air purifier and measurements of the size-dependent filtration efficiency were made, using the AAC to select monodisperse test particles by aerodynamic diameter. The performance of the air purifier was assessed by comparing size-dependent penetration measurements with the full real-world ambient spectra and accounting for the air exchange rate between the inside and outside of the room.
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A NEW METHODOLOGY FOR CONTINUOUS SCANNING OF PARTICLE
AERODYNAMIC DIAMETER AND APPLICATION TO FILTRATION
PERFORMANCE ASSESSMENT OF A ROOM AIR PURIFIER
Simon Payne1, Tyler Johnson2, Jonathan Symonds1
1 Cambustion Ltd., Cambridge, UK
2 Department of Engineering, University of Cambridge, UK
ABSTRACT
The Aerodynamic Aerosol Classifier (AAC) is a novel instrument that classifies
particles based on their aerodynamic diameter. This is accomplished by passing the
aerosol between spinning concentric cylinders with a coaxial sheath flow. Particles
that have aerodynamic diameters larger than the AAC setpoint are dominated by the
centrifugal force and impact the outer cylinder surface, while smaller particles remain
entrained in the sheath flow; only particles with a narrow range of aerodynamic
diameters pass through the AAC classifier. Particle sizes between 25 nm and
6.7 microns can be selected independent of the aerosol charge state, with a high
transmission efficiency limited only by diffusion and impaction losses.
This technique can be used to measure an aerosol’s aerodynamic size distribution by
stepping the AAC setpoint while recording the classified particle number
concentration. This stepping procedure requires long measurement times to achieve
reasonable spectral resolutions. To overcome this limitation, a scanning AAC
inversion was developed. Following a similar methodology as the Scanning Mobility
Particle Sizer (SMPS) inversion, this new approach allows the aerodynamic size
distribution to be continuously measured by varying the classifier speed while
measuring the classified particle concentration. By exponentially ramping the
classifier speed, the change in the centrifugal force a particle experiences during its
classifier residence time is independent of its inlet time. Furthermore, when the scan
time is sufficiently longer than the scan speed ramping constant, the scanning AAC
transfer function converges to the same shape as the steady state transfer function.
This new methodology is called the “Scanning Aerodynamic Size Spectrometer”
(SASS).
Application of the SASS is demonstrated by collecting accelerated measurements of
the ambient air particle size distributions in a room before, during and after operation
of a commercial room air purifier. Additionally, a filter sample was taken from the air
purifier and measurements of the size-dependent filtration efficiency were made,
using the AAC to select monodisperse test particles by aerodynamic diameter. The
performance of the air purifier was assessed by comparing size-dependent
penetration measurements with the full real-world ambient spectra and accounting for
the air exchange rate between the inside and outside of the room.
KEYWORDS
Aerodynamic Diameter, Aerosol, Air Filtration,
Classifier, Filtration Efficiency, Particle Size
INTRODUCTION
Developed by Tavakoli and Olfert (2013), the Aerodynamic Aerosol Classifier (AAC) uses a centrifugal
force and sheath flow between two concentric rotating cylinders to produce a truly monodisperse
aerosol classified by aerodynamic diameter with a range from 25 nm to 6.8 m. The instrument is
unique in being able to produce a stream of particles of known finite aerodynamic diameter; other
technologies such as impactors and virtual impactors provide either an upper or lower cut.
Aerodynamic diameter is an important equivalent particle size for characterising aerosol flow through
filter media, since it relates to the relaxation time of particles as flow conditions change. The particle
relaxation time,
, can be expressed in terms of aerodynamic diameter,
da
, as follows:
 



where
m
is the particle mass,
B
is the particle mobility,
Cc
is the Cunningham slip correction,
is the
dynamic viscosity of the carrier gas and
0
is unit density.
Unlike the differential mobility analyser (DMA), size classification by the AAC is independent of particle
charge state; this means there are no losses in throughput associated with charging efficiency and no
multiple charging peaks. Applications where the AAC has already found use as a DMA alternative
include aerosol charger efficiency testing (Johnson, et al., 2018), calibration of the condensation
particle counter (CPC) (Symonds, 2018) and filter penetration measurements (Payne, Irwin, Johnson,
& Symonds, 2018).
When paired with a CPC, the AAC can step scan the cylinder speed to produce aerodynamic size
distributions (Johnson, Irwin, Symonds, Olfert, & Boies, 2018). A new development is the ability to
conduct continuous scanning with ramping of the cylinder speed for higher spectral resolutions and
faster scans (Johnson, Symonds, Olfert, & Boies, 2019). This set-up forms the aerodynamic
alternative to the Scanning Mobility Particle Sizer (SMPS), which has been conventionally used in
aerosol studies, but the AAC’s scanning offers a wider size range and eliminates the SMPS’ needs for
a radioactive or X-ray source and charge correction.
In this paper, a continuous scanning AAC is presented which is henceforth referred to as the
“Scanning Aerodynamic Size Spectrometer” (SASS). Its application is demonstrated by measuring
the evolution of the ambient particle size distribution in a room before, during and after operation of an
air purifier. To support analysis of the scan data, measurements of particle penetration are made on a
filter sample from the air purifier using the AAC as a monodisperse particle selector, following the
same methodology presented previously at FILTECH (Payne, Irwin, Johnson, & Symonds, 2018).
METHOD
Summary of new continuous scanning technique
The continuous scanning AAC inversion was developed by Johnson et al. (2019) according to the
SMPS methodology devised by Wang and Flagan (1990). The aim of the SMPS was to overcome the
following challenges in the step scanning Differential Mobility Particle Sizer (DMPS):
Long measurement times to characterize a particle size distribution (more than 10 minutes)
Low spectral resolution (tens of points for multiple decades)
Parallel challenges exist for the step scanning mode of the AAC. For continuous scanning with an
SMPS, the voltage is ramped, whereas with the SASS, the rotational speed of the cylinders,
, must
be ramped. This means the forces acting on a particle vary during its residence time in the classifier.
Similar to the electric field in the DMA, the following condition applies: the ratio of the centrifugal field
in the AAC at a specific inlet time
tin
to the field at time
tin+t
must depend only on the particle
residence time and not on the time point in the scan at which the particle enters the classifier. This
condition is satisfied by configuring the classifier speed so that it follows an exponential function over
the scan time (Johnson, Symonds, Olfert, & Boies, 2019):
 

where:


The required classifier rotational speed,
, and acceleration profile during scanning is only a function
of the start and end speeds
start
and
end
(i.e. particle relaxation start and end setpoints) and the scan
time,
ts
.
The challenge with the AAC is that unlike the DMA, it has inertia to overcome and finite motor power.
The maximum acceleration at the fast (small sized) end of the scan effectively determines a lower limit
for the duration of an accurate scan: if the measurement time is too short, it will not be possible for the
cylinder rotational speed to follow the exponential profile at the fast end of the scan, the assumption
about particle trajectories will cease to be true and the scan data will not be valid.
By implementing this exponential speed function, Johnson et al. (2019) determined that the scanning
AAC transfer function converges to the same shape as the steady-state transfer function and that for
sufficiently long scans, the scanning AAC balanced-flow inversion is the same as the steady-state (i.e.
stepping) AAC balanced-flow inversion derived in a previous study (Johnson, Irwin, Symonds, Olfert,
& Boies, 2018).
Subsequently, Johnson et al. (2019) compared particle size distribution data for continuous scanning
versus step scanning and found that the SASS methodology reduced measurement times by
approximately a factor of two over the stepping AAC, while increasing the spectral resolution by a
factor of six or higher. For spherical dioctyl sebacate (DOS) particles, the most stable aerosol tested,
they found that SASS measurements agreed within 2% of the count median diameter, geometric
standard deviation and total number determined by the stepping AAC. The agreement between the
two techniques for non-spherical soot and sodium chloride (NaCl) particles varied from 0.4% to 11.3%
and was limited by the stability of the aerosol sources.
Air purifier
The effectiveness of a portable air purifier was investigated as an example application of the SASS.
The subject of these experiments was the DeLonghi AC150 air purifier, which has a four stage
filtration system illustrated in Figure 1 and is recommended for use in rooms up to 40 m2 in area. It
was operated at 160 m3/hr, which is the maximum of its three fan speed settings.
A key performance metric is the Clean Air Delivery Rate (CADR), which is assigned to commercial air
purifiers based on independent tests carried out for the Association of Home Appliance Manufacturers
(AHAM). The AHAM procedure uses a sealed chamber (measuring 11.8m2 in floor area and 2.4m in
height) with recirculating air, with the CADR test conducted under conditions of controlled temperature
and humidity (Association of Home Appliance Manufacturers, 2013). The CADR is the product of the
highest fan speed setting and the removal efficiency over a 10 or 20 minute period for three particle
types (and associated size ranges): 1) smoke produced by burning cigarette tobacco, 2) commercially
available test dust and 3) non-defatted paper mulberry pollen.
The CADR values for the AC150 (confirmed by DeLonghi UK and correct for the highest fan speed
setting of 160 m3/hr) are as follows:
1. Smoke 90 nm 1 m: 127 m3/hr (removal efficiency over 20 min = 0.794)
2. Dust 500 nm 3 m: 143 m3/hr (removal efficiency over 20 min = 0.894)
3. Pollen 5-11 m: 108 m3/hr (removal efficiency over 10 min = 0.675)
Note: CADR values are a metric for the performance of an air purifier as a complete system, and not
directly relatable to the air flow field in the test room or to the characteristics of any particular particle
removal methodology (Association of Home Appliance Manufacturers, 2013).
Figure 1: DeLonghi AC150 air purifier (left) and exploded schematic of its filtration stages (right)
The area of the pleated HEPA filter within the DeLonghi AC150 is 0.83 m2 when unfolded, meaning
at 160 m3/hr the filter face velocity is 5.4 cm/s (correct at ambient temperature & pressure) or 5.0 cm/s
at standard temperature and pressure (STP) i.e. 0°C and 1.013 bar(a). This same face velocity was
set for the size-selected NaCl and DOS experiments using filter samples cut and sealed in a 47mm
filter holder, following the exact same procedure for AAC filter testing reported at the previous year’s
conference (Payne, et al., 2018).
The AC150 model has an ioniser function, which releases negative ions into the outlet flow (to
encourage agglomeration of particles in the room air), but this was not activated; the pre-filter screen
shown in Figure 1 contains a coarse mesh to capture large dust fragments and hair, but this was
removed. This is because particle removal by the pleated particle filter is of primary interest in this
study. A new pleated filter was installed in the unit prior to recording room air scans.
Filter penetration with size-classified particles
Polydisperse aerosols of sodium chloride (NaCl) and dioctyl sebacate (DOS) were generated by
atomising solutions using a BGI Collison nebuliser. NaCl is the solid aerosol specified for filter testing
in numerous international standards and a solution was prepared by dissolving 1% NaCl by weight in
deionised water. The NaCl aerosol was then dried in a desiccating column filled with silica gel beads
before entering the classifier. DOS was selected as a second aerosol because it provided a
distribution with a significantly larger count median diameter and forms particles of known spherical
morphology and density (914 kg/m3). AAC step scans of both aerosols are shown in Figure 2 and
were recorded in conjunction with a TSI 3775 Condensation Particle Counter (CPC).
Figure 2: AAC scans of NaCl and DOS particle size distributions (both corrected for dilution)
recorded at 0.3 lpm sample flow and 3 lpm sheath flow
In common with usual flow setpoints for size distribution scanning, a constant 10:1 sheath:sample flow
ratio was maintained for particle size selection. At reference classifier conditions (0°C and 1.013
bar(a)), the AAC can classify aerodynamic particle diameters from 32 nm to 3 m at low flow (0.3/3.0
lpm sample/sheath flow) and from 202 nm to 6.8 m at high flow (1.5/15 lpm sample/sheath flow). The
lower size limit of the AAC is sensitive to particle diffusion and the maximum obtainable rotational
speed (this can be brought down to 25 nm if the sheath flow is reduced by approximately 25% at the
maximum speed, which will broaden the transfer function). The maximum selected aerodynamic
diameter for these measurements was 3 m, which is the upper size limit of the 3775 CPC.
The procedure adhered to the short-term particle penetration test outlined in Clause 8.2 in ISO 16900-
3 (2012) but for monodisperse aerosol. As shown in Figure 3, the AAC output mixes with HEPA-
filtered make-up air (to establish the correct filter face velocity), which is supplied by a compressed
zero air cylinder. Particle number upstream of the filter was recorded by bypassing the filter holder and
directing flow through an equivalent length tube. The percent penetration at each particle size was
calculated as the ratio of down- to upstream concentrations measured alternately with the same 3775
CPC.
0.00E+00
5.00E+07
1.00E+08
1.50E+08
2.00E+08
2.50E+08
3.00E+08
0.00E+00
2.50E+06
5.00E+06
7.50E+06
1.00E+07
1.25E+07
1.50E+07
0.01 0.1 110
DOS size spectral density (dN/dLog(Da)/cc)
NaCl size spectral density (dN/dLog(Da)/cc)
Aerodynamic diameter (m)
NaCl
DOS
Figure 3: Experimental schematic for classified aerosol filter testing
Room air scans
Configuration of the SASS requires careful selection of scan parameters for accurate results, which
depend on the specified size range and the transfer tube to the CPC. The minimum time of a scan
also depends on the tightness of the drive belts and the age and wear on the motor and bearings, due
to the maximum achievable acceleration of the cylinder rotation towards the fast end of the scan.
In practice, the shortest possible scan time for a specified size range is best found by trial and error,
which is facilitated by a cylinder speed lag warning given by the AAC interface and written to the data
file. Likewise, the delay time (which refers to the time taken for the CPC to respond to changes in the
concentration of particles exiting the classifier) is best determined empirically for a given length of
transfer tube; this is achieved by comparing two bi-directional scans (one going up in cylinder speed,
the other going down) of a monodisperse aerosol (such as polystyrene latex spheres) and ensuring
that the peaks are in alignment.
For these experiments, continuous scanning was performed between aerodynamic diameters of
30 nm and 500 nm (above which there was no appreciable concentration of particles in the room) at a
spectral resolution of 150 data points per decade of size and a scan duration of 6 minutes. The 3775
CPC was used as the particle detector. A correction devised by Johnson et al. (2018) was applied to
all scan data to account for particle diffusion and impaction losses in the classifier, as well as spectral
broadening.
The room on Cambustion premises selected for these experiments is representative of an average
home living room in size, measuring 4.50 m by 4.25 m (floor area = 19.1 m2) and 2.45 m in height; the
enclosed volume is 46.9 m3. As shown in Figure 4, the room has an internal door and two windows, all
of which were closed during scanning (the CPC exhaust tube was routed through the keyhole of the
door and out of a window in an adjacent room). The room functions as a storage area and there are
shelves and filing cabinets along each wall (which potentially serve as surfaces for particle capture).
The SASS and air purifier were positioned at opposite sides of a free-standing shelving unit in the
centre of the room. The SASS was placed on a table and a 0.2 m long silicone tube on the AAC inlet
was held in position with a small clamp so that the tube inlet faced the centre of the room and was
approximately 1 m above the floor (a typical head height for a sitting person). The air purifier was
placed on the floor and faced the centre of the room (the angle between its two inlet flows on either
side of the front panel is 90°), while the filtered air is discharged from the top of the unit in an upwards
direction.
HEPA
HEPA
Mass flow
controller
Mass flow
controller
Aerosol
sample
Compressed
zero air
47 mm
filter holder
Neutraliser
Setpoint da
Figure 4: Schematic of room used for AAC continuous scanning with approximate positions of the
SASS and air purifier (inlet flows are indicated by arrows)
The room was left undisturbed during the days when scans were run. A series of 100 consecutive bi-
directional scans (each one 6 minutes in duration) was requested in the AAC interface and started at
the beginning of each day. After a period of a few hours had elapsed, the DeLonghi AC150 air purifier
was remotely activated on its highest fan speed setting of 160 m3/hr. The air purifier has a timer
function and this was set to stop the fan after 2 hours’ operation. Scans were left to run for several
hours afterwards to monitor the evolution of the particle size distribution without active filtration, as air
was exchanged with the outside (through gaps around the door, windows and floor etc.).
RESULTS
Filter penetration curves
Measurements of NaCl and DOS particle penetration through a sample of the pleated filter from the
DeLonghi AC150 air purifier are plotted in Figure 5. At the same filter face velocity of 5 cm/s at STP,
the results for a 3M 8710E face mask from the AAC filter testing study presented previously at
FILTECH (Payne, Irwin, Johnson, & Symonds, 2018) are also plotted for comparison. For each
penetration value the error bars represent a two-sided 95% confidence interval, which was calculated
in accordance with the specifications for particle counting statistics in Clause 7 of ISO 29463-2 (2011),
based on the Poisson distribution.
Penetration of DOS particles through the air purifier filter is higher than NaCl at the same aerodynamic
diameter. In contrast, it was previously found that DOS penetration through the face mask filter was
lower than NaCl for >100 nm where the interception mechanism is dominant. The greater open
Air
purifier
4.25 m
4.50 m
fraction of the filter in the purifier versus the face mask means the collection efficiency of interception
is reduced at the same particle size and the tail end of the diffusion efficiency curve is more evident
here. Regarding diffusion, there was a significantly higher collection efficiency of NaCl than DOS by
the fibres in the purifier filter. The bulk density of DOS particles (914 kg/m3) is less than half that of
NaCl (2160 kg/m3) meaning at the same aerodynamic diameter, the mobility equivalent diameter of
NaCl particles is substantially smaller.
Figure 5: Penetration of AAC-classified particles from two aerosol sources through filter samples
from DeLonghi AC150 air purifier and 3M 8710E face mask
Effect of purifier on particles in room air
SASS data were acquired on three separate days within the same week in June 2019; the total
number concentration of ambient particles (corrected for losses in the AAC) is plotted against time for
each day in Figure 6. Changes in particle concentration independent of the action of the air purifier
can generally be attributed to air exchange, particle agglomeration and surface deposition.
On 10 June and 12 June, the total particle number begins to plateau after 2 hours’ operation of the
purifier. The ratio of the minimum particle level to the prior ambient level, multiplied by the CADR for
smoke (which is the most relevant of the 3 CADR values for the size spectrum present in the room air),
results in an estimate for the air exchange rate of ~25 m3/hr, which is a little over half the volume of
the room per hour. On 14 June, the total particle count begins to increase after 1 hour’s operation of
the air purifier, which suggests a significant concentration of new particles was generated outside the
room at this time.
0%
5%
10%
15%
20%
25%
30%
0.01 0.1 1 10
Number penetration
Aerodynamic diameter (m)
DOS @ 5 cm/s (STP),
DeLonghi AC150
HEPA filter
NaCl @ 5 cm/s (STP),
DeLonghi AC150
HEPA filter
NaCl @ 5 cm/s (STP),
3M 8710E face mask
Figure 6: Total particle number per cubic centimetre during three separate days of testing (time-
aligned for the 2 hour period during which the air purifier was operated)
A portion of back-to-back scans for each day are shown in Figure 7, beginning with the size
distribution recorded immediately before the air purifier was activated. These spectra are multi-modal;
on all three days the largest peak occurs between 70 nm and 90 nm, which likely indicates that engine
exhaust particles are the primary source. The room is located above a “Goods In” entrance where
diesel vans and trucks regularly stop it was noted there was a particular high frequency of deliveries
on 14 June. A peak between 150 nm and 250 nm is also present on all three days, probably
representing aged particulate matter that has agglomerated. In all cases the air purifier substantially
reduces the spectral density at all sizes within 20 minutes.
The SASS data were segregated by particle aerodynamic diameter (by integration over selected size
channels) and in Figure 8 the particle concentration by size is expressed as a fraction of the initial
concentration that was present just before the air purifier was switched on. These data represent a
complex relationship involving the filtration efficiency of the pleated filter in the purifier, the air flow field
and particle dynamics in the room and the air exchange (i.e. relatively clean air leaving the room and
particle-laden air migrating in). The results are generally consistent between the three days of testing,
mostly approaching a value between 0.80 and 0.95 for aerodynamic diameters above 100 nm. The net
removal is significantly lower for smaller sizes, which may be primarily related to the characteristics of
the purifier filter: the AAC-classified penetration data in Figure 5 indicated a most penetrating particle
size of approximately 100 nm for NaCl and possibly less than 50 nm for DOS. On 14 June, the net
particle removal fraction decreased at all sizes relative to the other two days (especially after 1 hour of
purifier operation), which was likely due to an idling diesel truck outside that caused an influx of high
concentration aerosol.
10
100
1000
10000
0 1 2 3 4 5 6 7 8 9
Total particle number /cc
Time elapsed (hours)
10 June
12 June
14 June
Air purifier on Air purifier off
Figure 7: Consecutive SASS scans of room air showing particle removal by the air purifier over a
48-minute period
0.0E+00
2.0E+02
4.0E+02
6.0E+02
8.0E+02
1.0E+03
1.2E+03
1.4E+03
1.6E+03
1.8E+03
2.0E+03
2.2E+03
10 100 1000
Size spectral density (dN/dLog(Da)/cc)
Particle aerodynamic diameter (nm)
Before air purifier switched on
0-6 min
6-12 min
12-18 min
18-24 min
24-30 min
30-36 min
36-42 min
42-48 min
10 June
Time
0.0E+00
2.0E+02
4.0E+02
6.0E+02
8.0E+02
1.0E+03
1.2E+03
1.4E+03
1.6E+03
1.8E+03
2.0E+03
2.2E+03
10 100 1000
Size spectral density (dN/dLog(Da)/cc)
Particle aerodynamic diameter (nm)
Before air purifier switched on
0-6 min
6-12 min
12-18 min
18-24 min
24-30 min
30-36 min
36-42 min
42-48 min
12 June
Time
0.0E+00
2.0E+02
4.0E+02
6.0E+02
8.0E+02
1.0E+03
1.2E+03
1.4E+03
1.6E+03
1.8E+03
2.0E+03
2.2E+03
10 100 1000
Size spectral density (dN/dLog(Da)/cc)
Particle aerodynamic diameter (nm)
Before air purifier switched on
0-6 min
6-12 min
12-18 min
18-24 min
24-30 min
30-36 min
36-42 min
42-48 min
Time
14 June
Figure 8: Fraction of size-segregated particles removed by air purifier against air exchange
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
020 40 60 80 100
Particle fraction removed since air purifier switched on
Time elapsed (min)
37 nm
47 nm
59 nm
74 nm
92 nm
112 nm
137 nm
165 nm
198 nm
235 nm
278 nm
327 nm
10 June
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
020 40 60 80 100
Particle fraction removed since air purifier switched on
Time elapsed (min)
37 nm
47 nm
59 nm
74 nm
92 nm
112 nm
137 nm
165 nm
198 nm
235 nm
278 nm
327 nm
12 June
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
020 40 60 80 100
Particle fraction removed since air purifier switched on
Time elapsed (min)
37 nm
47 nm
59 nm
74 nm
92 nm
112 nm
137 nm
165 nm
198 nm
235 nm
278 nm
327 nm
14 June
Figure 9: SASS scans of room air after the air purifier switched itself off (having run for 2 hours),
showing replenishment of particles over a 3 hour period due to air exchange
0.0E+00
2.0E+02
4.0E+02
6.0E+02
8.0E+02
1.0E+03
1.2E+03
1.4E+03
1.6E+03
1.8E+03
2.0E+03
2.2E+03
10 100 1000
Size spectral density (dN/dLog(Da)/cc)
Particle aerodynamic diameter (nm)
Before air purifier switched off
18-24 min
42-48 min
66-72 min
90-96 min
114-120 min
138-144 min
152-158 min
176-182 min
10 June
Time
0.0E+00
2.0E+02
4.0E+02
6.0E+02
8.0E+02
1.0E+03
1.2E+03
1.4E+03
1.6E+03
1.8E+03
2.0E+03
2.2E+03
10 100 1000
Size spectral density (dN/dLog(Da)/cc)
Particle aerodynamic diameter (nm)
Before air purifier switched off
18-24 min
42-48 min
66-72 min
90-96 min
114-120 min
138-144 min
152-158 min
176-182 min
12 June
Time
0.0E+00
5.0E+02
1.0E+03
1.5E+03
2.0E+03
2.5E+03
3.0E+03
10 100 1000
Size spectral density (dN/dLog(Da)/cc)
Particle aerodynamic diameter (nm)
Before air purifier switched off
18-24 min
42-48 min
66-72 min
90-96 min
114-120 min
138-144 min
152-158 min
176-182 min
14 June
Time
Figure 9 shows a selection of SASS scans equally spaced in time, from the point at which the air
purifier switched itself off to 3 hours later in the day. The results vary widely between the three days of
testing and are clearly dominated by the air exchange and inwards migration of new particulate matter,
with the highest spectral density at 75-90 nm (again, strongly indicative of engine exhaust particles).
CONCLUSIONS
The aerodynamic size distribution of an aerosol can be measured by continuously ramping the AAC
classifier speed along an exponential function in a configuration called the Scanning Aerodynamic
Size Spectrometer” (SASS). Continuous scanning offers the advantages over step scanning of
reduced measurement times and significantly higher spectral resolution.
Application of the SASS was demonstrated by tracking particle size spectra in a room (equivalent to
an average home living room in size) as particles were continually filtered by an air purifier and
replenished due to air exchange with the outside, which brought in new particulate matter that likely
originated from diesel engine exhaust. The air purifier achieved a net removal fraction of between 0.80
and 0.95 for aerodynamic diameters above 100 nm over three separate days of testing. A reduced
level of removal at smaller sizes was at least partly due to the characteristics of the particle filter inside
the purifier; a previously presented AAC filter testing methodology was used to show that the most
penetrating particle size is approximately 100 nm for NaCl particles and less than 50 nm for DOS
particles.
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Association of Home Appliance Manufacturers. (2013). Method for Measuring Performance of
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29463:2011 High-efficiency filters and filter media for removing particles in air.
ISO. (2012). Part 3: Determination of particle filter penetration. In ISO 16900:2012 Respiratory
protective devices - Methods of test and test equipment.
Johnson, T. J., Irwin, M., Symonds, J. P., Olfert, J. S., & Boies, A. M. (2018). Measuring Aerosol Size
Distributions with the Aerodynamic Aerosol Classifier. Aerosol Science and Technology, 52(6),
1-11.
Johnson, T. J., Nishida, R. T., Irwin, M., Symonds, J. P., Olfert, J. S., & Boies, A. M. (2018). Using the
Aerodynamic Aerosol Classifier to Measure Particle Charge Distribution. Aerosol Technology.
Bilbao, Spain.
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Aerodynamic Aerosol Classifier. 11th Asian Aerosol Conference. Hong Kong.
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Conference Paper
Full-text available
*** Note: the accompanying slideshow is accessed via the "Linked Data" tab below *** The Aerodynamic Aerosol Classifier (AAC) uses a centrifugal force and sheath flow between two concentric rotating cylinders to produce a truly monodisperse aerosol classified by aerodynamic diameter with a range from 25 nm to 6.8 µm. The instrument is unique in being able to produce a stream of particles of known finite aerodynamic diameter; other technologies such as impactors and virtual impactors provide either an upper or lower cut. Since the classification technique is independent of particle charge state, there are no losses in throughput associated with charging efficiency, and no multiple charging peaks such as those commonly associated with the differential mobility analyser (DMA). Samples from two respiratory filtering half masks conforming to international standards for personal protective equipment were mounted in an in-line filter holder. These were placed downstream of the AAC which was run at a series of rotational speeds and sheath flows to select aerodynamic diameters from two atomised aerosol sources: sodium chloride (NaCl) and dioctyl sebacate (DOS). The upstream and downstream particle number concentrations were measured using a condensation particle counter (CPC). Tests at each particle size were run back-to-back replacing the AAC with a DMA long column, which was configured to select particles of the same aerodynamic diameter when converted from electrical mobility size space. This enabled direct comparison of transmission efficiency and filter penetration behaviour between the two methods of classification. It was found that the classifier throughput of the AAC was 1.5 to 5.5 times higher than the DMA across the particle sizes tested from both aerosols. Filter penetration curves were generally in close agreement; in specific cases where there was a disparity, multiple charging from the DMA was a possible explanation. To investigate this effect, a particle diameter was selected from the left side of the DOS size distribution so that multiply-charged particles were drawn over the peak. The DMA output was then scanned with the AAC either side of a face mask sample which showed the presence of doubly and triply charged particles from the DMA downstream of the filter, leading to error in the penetration calculation.
Article
The Aerodynamic Aerosol Classifier (AAC) is a novel instrument that selects aerosol particles based on their relaxation time or aerodynamic diameter. Additional theory and characterization is required to allow the AAC to accurately measure an aerosol’s aerodynamic size distribution by stepping while connected to a particle counter (such as a Condensation Particle Counter, CPC). To achieve this goal, this study characterized the AAC transfer function (from 32 nm to 3 μm) using tandem AACs and comparing the experimental results to the theoretical tandem deconvolution. These results show that the AAC transmission efficiency is 2.6–5.1 times higher than a combined Krypton-85 radioactive neutralizer and Differential Mobility Analyzer (DMA), as the AAC classifies particles independent of their charge state. However, the AAC transfer function is 1.3–1.9 times broader than predicted by theory. Using this characterized transfer function, the theory to measure an aerosol’s aerodynamic size distribution using an AAC and particle counter was developed. The transfer function characterization and stepping deconvolution were validated by comparing the size distribution measured with an AAC-CPC system against parallel measurements taken with a Scanning Mobility Particle Sizer (SMPS), CPC, and Electrical Low Pressure Impactor (ELPI). The effects of changing AAC classifier conditions on the particle selected were also investigated and found to be small (<1.5%) within its operating range. Copyright © 2018 American Association for Aerosol Research
Article
A new aerosol particle classifier, the aerodynamic aerosol classifier (AAC), is presented and its classifying characteristics are determined theoretically. The AAC consists of two rotating coaxial cylinders rotating at the same angular velocity. The aerosol to be classified enters through a gap in the inner cylinder and is carried axially by particle-free sheath flow. The centrifugal force causes the particles between the rotating cylinders to move in the radial direction and particles of a narrow range of particle relaxation times exit the classifier through a gap in the outer cylinder with the sample flow. Particles with larger relaxation times impact and adhere to the outer cylinder and particles with smaller relaxation times exit the classifier with the exhaust flow. Thus, the aerosol is classified by particle relaxation time from which the aerodynamic equivalent diameter can easily be found. Four theoretical models of the instrument transfer function are developed. Analytical particle streamline models (with and without the effects of particle diffusion), like those often used for mobility classifiers, are developed for the case when the centrifugal acceleration field is assumed to be uniform in the radial direction. More accurate models are developed when this assumption is not made. These models are the analytical limiting trajectory model which neglects the effects of diffusion and a numerical convective diffusion model that does not. It is shown that these models agree quite well when the gap between the cylinders is small compared to the radii of the cylinders. The models show that, theoretically, the AAC has a relatively wide classification range and high resolution.Copyright 2013 American Association for Aerosol Research
Using the Aerodynamic Aerosol Classifier to Measure Particle Charge Distribution
  • T J Johnson
  • R T Nishida
  • M Irwin
  • J P Symonds
  • J S Olfert
  • A M Boies
Johnson, T. J., Nishida, R. T., Irwin, M., Symonds, J. P., Olfert, J. S., & Boies, A. M. (2018). Using the Aerodynamic Aerosol Classifier to Measure Particle Charge Distribution. Aerosol Technology. Bilbao, Spain.
A New Method to Minimise Charge Uncertainty in Condensation Particle Counter Calibration when Using a Faraday-Cup Aerosol Electrometer
  • J P Symonds
Symonds, J. P. (2018). A New Method to Minimise Charge Uncertainty in Condensation Particle Counter Calibration when Using a Faraday-Cup Aerosol Electrometer. Aerosol Technology. Bilbao, Spain.
  • S C Wang
  • R C Flagan
Wang, S. C., & Flagan, R. C. (1990). Scanning Electrical Mobility Spectrometer. Aerosol Science and Technology, 13(2), 230-240.
Part 2: Aerosol production, measuring equipment and particle-counting statistics
  • Iso
ISO. (2011). Part 2: Aerosol production, measuring equipment and particle-counting statistics. In ISO 29463:2011 High-efficiency filters and filter media for removing particles in air.