Measurements and methods
Figure shows all the experiments from 2006 to 2013 at which
measurements were made with the HTDMA and CCNc instruments described below.
The measurements that are included in this study are labelled in bold in the
figure text. These include a total of eight locations, at two of which (Mace
Head and London), separate summer and winter measurement campaigns were
conducted. In each campaign, the measurements were conducted over three to
six weeks at a time. The measurements covered a range of different ambient
environments including marine (Discovery cruise, Mace Head, Weybourne),
tropical (Borneo, Amazonia), continental background (Hornisgrinde,
Chilbolton) and urban (London). These data sets were selected out of all those
in Fig. for the quality of the data and suitability of
measurement configuration for reconciliation study. The HTDMA and/or CCNc
measurement data collected in the other experiments shown in Fig. were less suited to hygroscopicity–CCN reconciliation.
For each experiment, CCN activity was measured as a function of
supersaturation and particle dry size using a Droplet Measurement
Technologies cloud condensation nuclei counter
CCNc;. The calibration and operation of the CCNc is
described fully by and
, with mostly the same methods used in all
projects. Briefly, a dried (<20% RH, relative humidity) monodisperse aerosol sample was
supplied by a differential mobility analyser (DMA) stepping discretely
through a range of sizes (the exception being Chilbolton, where the sample
was not dried). The sample was then split between the CCNc and a condensation
particle counter (CPC; TSI model 3010). The ratio of the number of CCN
(NCCN) to the total number concentration of aerosol particles (NCN)
is the fraction of particles activated (FA(S,D0)) at a given
supersaturation, S, and dry diameter, D0. The resulting activation
spectra (FA(S,D0) as a function of dry diameter, D0) can be used
to derive the diameter at which 50 % of the particles activate (D50) by
fitting a sigmoid curve function. The hygroscopicity parameter, κ, can
then be derived using the κ-Köhler model, and will be denoted by
κD50.
Hygroscopic growth factor distributions were measured during each experiment
using a Hygroscopicity Tandem Differential Mobility Analyser (HTDMA). Two
different instruments were used: the first (HTDMA1), developed by
, was used during the Discovery, Hornisgrinde, Borneo,
and Amazonia experiments, while the second (HTDMA2), developed by
, was used in the remaining experiments. In all cases,
calibrations were conducted as discussed by , and the
data were processed using the TDMAinv software described by
. In the HTDMA, a dry aerosol sample is size-selected
with the first DMA and then humidified to 90 % RH except at
Hornisgrinde where 86 % RH was used;. The second DMA is then
used to measure the size distribution of the humidified aerosol, to give the
distribution of Growth Factor (defined as the ratio of wet to dry aerosol
diameter) as a function of RH and dry diameter (GFRH,D0). For most of
the studies, 5 to 7 dry sizes were scanned in this way, ranging from 24 to
300 nm. Values of κ can be calculated from the mean growth factor
measurements as described by Eq. ():
S=GF‾3-1GF‾3-(1-κ)exp4σwMwRTρwD0GF‾,
where S is the supersaturation (RH/ 100%), GF‾ is the mean
growth factor, κ is the hygroscopicity parameter, σ is the
surface tension of water, Mw is the molar mass of water, R is the
universal gas constant, T is the temperature, ρw is the density of
water and D0 is the dry diameter. The κ derived from the growth
factor data will be denoted by κGF.
Map showing the locations of measurements. The labels name the
locations, projects and dates of the experiments. The data sets used in this
study are labelled in bold print.
A number of approaches can be taken to calculate total NCCN as a
function of supersaturation. From the CCNc data, the simplest way is to
integrate NCCN(S,D0) as a function of D0 for each set
supersaturation, Sset. Alternatively, the aerosol number size
distribution (as measured by the CPC on the DMA) can be integrated from the
largest size down to a threshold diameter (in this case, the D50 derived
from the activation spectra). For the HTDMA data, a threshold diameter can be
derived from the calculated κGF values for a given supersaturation,
and from this, NCCN can be calculated as before. By using the Sset
from the CCNc in deriving NCCN from the HTDMA, a direct comparison
between the instruments can be made. In this study, NCCN from the CCNc
data is derived from the aerosol size distribution and D50 and compared
with NCCN derived from the HTDMA data. κ values are also compared
between the instruments using the methods described above.
The calibration procedures employed in all experiments for both the CCNc and
HTDMA are rigorous and described in detail by . The DMA
upstream of the CCNc and the first DMA in the HTDMA were calibrated using
latex spheres. The HTDMA was operated for a few hours without humidification
every week or two, to calibrate for any offset between the two DMAs, and to
define the instrument's transfer function. Both the HTDMA and the CCNc were
generally calibrated at the start and end of each experiment using nebulised
ammonium sulfate. For the HTDMA, this calibration involved running a
humidogram: i.e. measuring the GF at a range of RHs at a fixed dry diameter
(typically 150 nm), and comparing to theoretical GF .
Corrections can then be made to the measured RH where necessary. The CCNc was
calibrated by sampling nebulised and dried monodisperse ammonium sulfate
from a DMA at 3–5 mobility diameters between 30 and 100 nm . At each
diameter the temperature gradient in the CCNc was stepped up and an
activation curve (CCN/CN) was derived. The temperature gradient at which 50 %
of the particles were counted as CCN was assumed to correspond to the
critical supersaturation. The temperature gradient to supersaturation
relation was then derived by a linear fit to the theoretical
critical supersaturation at each diameter.
Results and discussion
Size distribution box-and-whisker plots showing the median,
interquartile ranges and 5th and 95th percentile size distributions for each
measurement campaign.
The median and ranges of the aerosol size distributions for each campaign are
shown in Fig. . In all cases, these were derived from the
DMA and CPC attached to the CCNc. These show a wide variation in the aerosol
size distributions between the different campaigns, and a similarly wide
variation can be seen in the GF distributions from the HTDMA measurements,
which are shown in the Supplement for each experiment, and are
reported for 90 % RH at all locations (except Hornisgrinde, which is reported
at 86 % RH). The aerosol size distributions observed in London are similar to
previous measurements e.g., while the
GF distributions show an external mixture with hydrophobic (GF ≈1) and hygroscopic modes (GF=1.5), similar to other urban measurements
. At Mace Head, the winter measurements were dominated by
“modified marine” air masses, while the summer experiment saw a largely
“clean marine” fetch, and the measured size distributions were typical of
these respective air masses . The modified marine GF
distribution was dominated by a hydrophobic mode (GF ≈1.1), while
the clean marine had a strong sea salt mode (GF ≈2.2). Both
experiments exhibited a hygroscopic mode (GF = 1.5–1.7), which largely
dominated in the summer campaign but showed significant variability along
with the sea salt mode. Both the aerosol size distributions and the GF
distributions measured in the Amazon were typical at that site in the dry
season , but differed considerably from the other tropical
measurements at the Borneo site, which, by contrast, was strongly influenced
by marine air masses . In the Amazon, the GF distributions
show a persistent, internally mixed aerosol with GF 1.2–1.3, while in
Borneo, the dominant mode varied between GF 1.4–1.6 (depending on dry
size) with an occasional hydrophobic mode. From its location, Chilbolton is
regarded as a rural background site, and further analysis of other measurements
taken during this campaign (unpublished data) suggests the aerosol is largely
representative of regional properties, with only a small influence from local
sources. The GF distributions show a persistent external mixture with modes
around 1.1 and 1.5. The Discovery cruise took place off the coast of West
Africa, and over the course of the campaign, three distinct air masses were
seen: African, Continental (from Southern Europe) and Marine. These are not
separated out for the purposes of this study, and the size distribution in
Fig. represents the whole data set. Growth factors were
mostly around 1.7, and showed a largely internal mixture for most of the
experiment, except for a sporadic sea salt mode at the larger sizes. A more
in-depth examination of this is provided by .
Hornisgrinde is a mountaintop site, which was frequently in cloud during
measurements , and is described as “continental
background”. The GF distribution is more variable with time and dry size
that at some of the other experiments, ranging 1.1–1.4 (at 86 % RH). A
bimodal GF distribution can be seen sometimes at the larger dry sizes.
Finally Weybourne, while being coastal, can experience a variety of different
air masses, and did so during the experiment , and frequently
sees aged polluted plumes from the UK and mainland Europe. The GF
distributions show a dominant hygroscopic mode (which seems to vary diurnally
between 1.4 and 1.7), accompanied by a weaker hydrophobic mode. As with the
other campaigns, the Weybourne data set was considered as a whole for the
purpose of this study. The compilation of all these data sets therefore
provides a wide range of aerosol populations, typically present in the
atmosphere at different locations. From this, it should be possible to probe
whether this variation has any influence on the reconciliation.
For each measurement campaign, the mean values of NCCN and κ
derived from D50 and GF were found for each Sset, and the ratios
of these means are plotted in Fig. . The error bars
represent the standard deviation of these ratios, and hence show the
variation throughout a given experiment. In some campaigns, where the HTDMA
calibrations drifted between the start and end of the experiment, both were
applied and the spread is illustrated in Fig. as shaded
areas. The graphs show that the level of reconciliation varied greatly
between the different experiments, generally varying with supersaturation.
Poorest agreement between the HTDMA and CCNc across the range of
supersaturations was found in the measurements from Hornisgrinde, Borneo,
Chilbolton and the Discovery cruise. The other experiments largely showed
agreement within the error bars for at least some of the supersaturation
range. In general, there seems to be a tendency for the HTDMA measurements to
underestimate hygroscopicity compared to the CCNc, especially at lower
supersaturations, resulting in a ratio greater than one. The only exception
to this is the Borneo experiment, though it is not clear why this is the
case.
Ratios of mean D50 and GF derived (a) NCCN and (b) κ values as a function of Sset for each measurement campaign.
Error bars represent one standard deviation. The shaded areas represent the
spread of values due to differing HTDMA calibrations.
It is also not clear why the results for the Hornisgrinde and Discovery
cruise data sets stand out in the reconciliation in Fig. .
Possible reasons for discrepancies between CCNc and HTDMA derived κ
and NCCN for the Discovery, Hornisgrinde and Borneo data sets have been
discussed at length by and
, respectively, and they are likely to apply in
varying degrees to the other data sets. The discrepancies are described as
being due either to instrumental differences or assumptions made in the
model. Previously, discrepancies between measured and modelled CCN behaviour
have been attributed variously to particle surface tension at the point of
activation, changes in the kinetics of uptake in the instruments, or external
mixing.
When using the κ-Köhler model, the surface tension is often
assumed to be that of pure water, σ = 0.072 J m-2
. In reality, surface active compounds may
concentrate at the water–air interface of a deliquesced particle, suppressing
surface tension and affecting the CCN activity of the particle. A number of
studies have explored the effect of this assumption on reconciliation, and
have found either that reducing surface tension in the calculations would not
improve closure , or that unrealistic values of surface
tension would be required to account for discrepancies . Moreover, more recent work has demonstrated that
bulk-to-surface partitioning offsets most of the influence of any surface
tension reduction .
The κ-Köhler model also does not account for changes in solution
non-ideality as a function of saturation ratio. To date, it has been very
difficult to probe how κ varies as RH increases towards 100 % due to
the uncertainties in HTDMA instruments at high RH . Recent developments should make this possible.
The presence of slightly soluble compounds can influence the reconciliation,
by only contributing measurably to water uptake in supersaturated conditions.
This would result in an underestimate in NCCN from the HTDMA
measurements . Particle non-sphericity, and the effect this
has on their classification in DMAs, can also have the effect of suppressing
the calculated κ from both GF and CCN measurements. This is because
of the difference between a non-spherical particle's mobility diameter and
its volume equivalent diameter. In sensitivity studies, found
that the κ suppression was greater in GF calculations than from
measured CCN data, resulting again in an underestimate of hygroscopicity from
the HTDMA measurements compared to the CCNc measurements. These effects would
result in the hygroscopicity being underestimated by the GF calculations
compared to the CCNc derived values , and therefore may be
partly the reason why there is a tendency towards a greater than one ratio,
as seen in Fig. .
Instrumental differences mainly relate to the chemical behaviour of aerosols
and gases in the respective instruments. Growth factor may be underestimated
in the HTDMA if the residence time following humidification is too short to
reach equilibrium before sizing in the second DMA , leading
to an underestimate of hygroscopicity. In addition, volatile and
semi-volatile compounds can evaporate during the drying process. While the
HTDMA and CCNc use the same dryer in all these measurements, the subsequent
behaviour of the volatilised gases in the different conditions of each
instrument can lead to further discrepancies . For
example, the saturation column of the CCNc can act as a mist chamber, where
droplets take on soluble material from the gas phase, potentially increasing
the NCCN count. Indeed, the possible influences of semi-volatile
components on droplet activation and on reconciliation between sub- and
supersaturated measurements has been discussed by and the
impacts of semi-volatile co-condensation expanded by .
One possible reason for the higher discrepancy in the Chilbolton
reconciliation is the fact that the aerosol sample was not dried before
entering the instruments (Chilbolton was the only exception). The RH was
often above 50 % and as much as 70 %, and the DMAs were therefore not
selecting dry sizes. To test the effect of this, the values for the dry sizes
were reduced (and GF‾ increased) by a factor of 1.1, to simulate
dry aerosol sizes, and the analysis repeated to get the ratios. Figure S1 in the Supplement shows that this results in a substantial
improvement in the reconciliation, especially for the NCCN ratios. It
should be stated here that while the factor of 1.1 represents a realistic
value at the RH measured in the aerosol sample, it cannot be verified, nor
does it reflect the variability in inlet RH or κ, which would cause the
correction itself to vary. These new results therefore do not represent the
real ratios at Chilbolton. Nevertheless, this exercise illustrates the
importance of using dry aerosol samples for these measurements, however as
mentioned in the previous paragraph, drying can also lead to the removal of
volatile and semi-volatile compounds from the condensed phase. This is
potentially a very important artefact in these measurements, which may lead
to false agreement in reconciliation studies, and therefore requires further
study.
The aerosol mixing state might also affect agreement, since the methods
commonly used to derive hygroscopicity and NCCN with the HTDMA and CCNc
do not account for externally mixed aerosol, which can have different effects
in the two instruments. A number of studies have considered this, using
different methods to account for external mixing. Most of these
e.g. found that mixing state
has no effect on measurement reconciliation, however found that
it is important in obtaining agreement between between HTDMA and chemical
composition derived hygroscopicity. For this study the mixing state was
parameterised, using the HTDMA growth factor distribution, by the absolute
value of the mean growth factor subtracted from the peak growth factor.
Strong external mixing could be seen in the HTDMA measurements at Chilbolton
and London (Summer and Winter), and the mixing state parameter ranged 0.12–0.20. For
measurements that showed a lesser degree of external mixing (i.e. a
weaker secondary mode in the growth factor distribution; e.g. Borneo, Mace
Head), the mixing state parameter ranged between 0.06 and 0.12, and was less
than 0.05 for measurements showing a largely internally mixed aerosol sample
(e.g. Discovery cruise). accounted for external mixing
in their reconciliation study by defining a critical growth factor at each
dry diameter, above which particles activate at a given supersaturation. The
fraction of particles above this growth factor is the activated fraction,
thus providing an activation spectrum (FA(S,D0)) from which to
calculate D50 and hence NCCN as described above. For the CCNc,
external mixing can be taken into account by integrating NCCN(S,D0)
as a function of D0 for each Sset. The ratios of the mean values of
NCCN derived from each method were calculated and compared to those shown
in Fig. . No improvement was seen in reconciliation in
any of the data sets, suggesting that mixing state does not affect
hygroscopicity–CCN reconciliation, even when the degree of external mixing is
high.
As already mentioned, there is a tendency in some of the data sets shown in
Fig. for the ratios to increase with decreasing
supersaturation. A similar trend has also been observed in other studies
e.g., and has been explained as resulting from
greater uncertainties in the instrument at lower supersaturations. The
threshold diameter at these supersaturations is higher up in the tail of the
particle number size distribution, and so predictions are more sensitive to
the counting statistics in the size distribution.While this can explain the
wide variation in the measurements (shown as large error bars) that can be
seen here, it would not account for the bias (i.e. that NCCN(GF) should
be consistently less than NCCN(D50)). A bias at low supersaturations
due to uncertainties in the determination of the supersaturation would be eliminated by the
calibration method applied to these data sets, and so would not explain it.
Therefore, it is not clear what causes the larger bias at low
supersaturations.
This trend is not observed in the data sets that show the poorest agreement
(Discovery cruise, Hornisgrinde and Borneo), and it is noted that all these
measurements were conducted with the same HTDMA (HTDMA1). However the
measurements in Amazonia also employed HTDMA1 and these show relatively good
reconciliation, plus the trend of higher ratios at lower supersaturations.
The two HTDMAs were operated side by side, sampling ambient air in
Manchester, UK, along with a CCNc, in order to compare reconciliation
results. The derived NCCN and κ ratios are shown in Fig. S2. Better agreement is seen using HTDMA2, but
importantly, both exhibit the trend of increased ratios at lower
supersaturations that is seen in other data sets in Fig. .
This information shows that differences between campaigns in the relationship
between ratios of NCCN or κ and supersaturation cannot be
attributed to different instruments. A detailed analysis of differences
between HTDMA systems is provided by and
.
The wide range of locations from which the studies presented here derive make
it possible to explore whether different environments (characterised by
different aerosol populations) result in different degrees of reconciliation
in water uptake measurements. No common patterns could be seen in Fig. for measurements from similar environments, distinct
from others, so there appears to be no such dependency.
For each data set, NCCN was also calculated from both the HTDMA and CCNc
data using campaign averages of either κ (or D50 in the case of
the CCNc) or size distribution. The results are shown in the Supplement as box plots of NCCN as a function of supersaturation for each
method. In most of the data sets, averaging κ does not lead to a
significant change in mean NCCN(S) from either instrument, whereas
NCCN(S) derived using the mean size distribution shows a much reduced
variability. Taken in isolation, the data from a single instrument may imply
that NCCN is rather insensitive to κ, and hence chemical
composition and that, unsurprisingly, size distribution is more important for
predicting NCCN, in agreement with previous studies
e.g.. However, that NCCN derived from
different instruments frequently differs markedly indicates a strong
requirement to understand the processes leading to the discrepancies and
thereafter to define a protocol for reliable NCCN quantification in line
with our most informed understanding of the physical processes involved in
their measurement.