Introduction
Aerosol–cloud interactions are a major source of uncertainties in the
quantification of climate forcing of aerosols . The
wet size of an aerosol particle when at equilibrium with the environment is
governed by Köhler theory and depends on particle size
and composition. In the atmosphere, activation of cloud condensation nuclei
(CCN) is a competition between aerosol particles for water vapor, influenced
by dynamical processes and the kinetics of particle growth and dependent on
the updraft velocities, aerosol number concentrations and differences in size
and composition of aerosol particles . Although our
understanding of the processes involved in aerosol activation has increased
considerably in recent years , the inclusion of all the
detailed information that might be available about aerosol populations into
global and regional circulation models is often impractical. Thus,
assessments of the uncertainties derived from simplifications assumed are
relevant and potentially contribute to the discussion on the level of
sophistication required by general circulation models (GCMs) with the aim of
decreasing the uncertainties.
A large quantity of aerosol particles is generated globally by open biomass
burning , and the impacts of
smoke aerosols in climate, air quality and geochemistry have being addressed
in several studies and references
therein.
Vegetation fires plumes can be entrained into upper levels of the troposphere
and undergo long-range transport before being removed from the atmosphere if
conditions are favorable, e.g., when convection activity is high
. During the dry season
in South America, observation and numerical model results agree in that
biomass burning aerosol originated from extensive fires typically detected
over the Amazon and central Brazil regions, represents a significant fraction
of the aerosol burden in southern and southeastern parts of Brazil, in Uruguay
and in
northern Argentina
.
Even though a large fraction of biomass burning aerosols has low to moderate
hygroscopicity
,
biomass burning particles can act as CCN under sufficiently high atmospheric
water vapor supersaturations .
Therefore, CCN activation properties of pyrogenic particles are likely to be
relevant for the aerosol climate forcing.
Some external mixing in terms of hygroscopicity seems to be rather common in
aerosol populations, particularly over continents
. However, average hygroscopicity parameters
have been estimated from both observational and modeled data assuming
internal mixing for aerosols from the same emission source (e.g., biomass
burning), or even within the same geographical region
. Sensitivity of CCN activation to hygroscopic
mixing state under equilibrium conditions is also significant, and the
assumption of total internal mixing could result in an overestimation of the
CCN population that can range from 10 to 100 %
. The impact of mixing state
under dynamic conditions has, however, been less studied, and some evidence
suggests that conclusions from equilibrium conditions might not be directly
extrapolated to CCN activation during cloud formation
.
The aerosol particle's composition is known to influence the particle water
uptake and CCN activation .
Although the effects of composition on the cloud droplet number
concentrations are typically secondary when compared to those of population
number concentration and size distribution
, the
extent to which these effects can be safely neglected in GCMs is also yet
to be established. Droplet number concentrations were shown to be more
sensitive to the presence of organic content than to the updraft velocity in
some situations . On conditions typical of pyrocumulus
(number concentrations up to 105 cm-3 and updraft velocities up
to 20 ms-1), found that cloud droplet number
concentration was sensitive to compositional effects (hygroscopicity). For
three different ratios of the aerosol number concentrations to the updraft
velocity, and for a fixed aerosol size distribution, the authors found that
the sensitivity to hygroscopicity was low for medium to high hygroscopic
values, but moderate for very low and low hygroscopicity values
. Still, sensitivities to hygroscopicity are likely to be
tightly related to the position of the dry critical size of the smallest
activated particle within the overall size distribution of the aerosol
population, and significant sensitivities have been obtained for the
population of small aerosol particles with medium and high hygroscopicity
.
Aerosol particles with critical supersaturations smaller than the maximum
supersaturation reached within the cloud can nonetheless become interstitial
aerosols due to the evaporation and deactivation mechanisms described by
. These kinetic limitations, sometimes neglected in GCMs,
are expected to be large when significant aerosol loads are present
. Consequently, parameterizations that assume equilibrium
conditions overestimate CCN when kinetic limitations are important
. However, little is known about how kinetic
limitations are related with the particle hygroscopicity, although a relation
between the timescale of the components solubility and activation has been
reported .
On the other hand, several observational biomass burning studies conducted in
the Amazon region reported rather similar number size distributions for
biomass burning aerosols within the boundary layer
. In
terms of hygroscopicity, these smoke particles have been found to be
externally mixed . Their population effective
hygroscopicity parameter, converted from the original data using expressions
suggested by , ranged between 0.05 and 0.13
; these compare well with observed values for
biomass burning aerosols but are rather on the lower side of the range of
values reported elsewhere. Reported values of the hygroscopicity parameter
for freshly emitted smoke particles in biomass burning laboratory experiments
reached values up to 0.6, although a significant number of data indicated
values between 0.02 and 0.2, with wood species and smoldering fires producing
the less hygroscopic particles
. An average
hygroscopicity parameter of 0.21 was obtained for a 4-day biomass burning
episode near Guangzhou, China, using airborne data . The
hygroscopicity parameter obtained from CCN airborne measurements for boreal
fires biomass burning aerosols in Canada was 0.18 for both recently emitted
and aged aerosols, while the values estimated assuming an average chemical
composition were, on average, 0.11 for fresh aerosol particles and 0.24 for
aged ones, both within the level of variability in the value estimated from
CCN measurements . A recent study of the hygroscopicity of
recently emitted and aged smoke particles reported ranging between 0.05 and 0.1
for the same parameter in Thailand .
In the present study, we used an adiabatic cloud model to simulate the CCN
activation of biomass burning particles, aiming to contribute to the
understanding of the possible impact of different hygroscopicity values,
mixing state and kinetic limitations in the CCN activated fraction. The
modeling approach followed is described in Sect. 2. According to the
available observations of biomass burning aerosols in the Amazon region,
three typical situations in terms of size distributions and other aerosol
parameters were considered in the definition of the case studies and other
simulation parameters, as described in Sect. 3. Finally, the results from the
cloud parcel model and our conclusions are discussed in Sects. 4 and 5.
Definition of case studies and simulation parameters
In this work, three hypothetical different size distributions were defined as
case studies for the cloud model simulations (Table ). The
corresponding number size distributions are depicted in Fig. .
The parameters of the selected size distributions were chosen as to resemble
biomass burning aerosol observations in Amazonia (resumed in Table S1 of the
Supplement) while trying to minimize the impact of particle size and standard
deviation. The first case is a moderately polluted case with 5000 cm-3
particles in the Aitken mode, and 1000 cm-3 in the accumulation
modes, respectively (MP5,1) (Fig. a). Case MP5,1 is
similar to the observed distribution during the SAMBBA experiment (South
American Biomass Burning Analysis, 2012) . The second is a case
study with the same number concentration than MP5,1, but with higher
number of particles in the accumulation mode, with 1000 and
5000 cm-3 in the accumulation and Aitken modes, respectively
(MP1,5) (Fig. b). The size distribution of case MP1,5
is comparable to the observed during LBA-SMOCC (Large-Scale Biosphere
Atmosphere Experiment in Amazonia – Smoke Aerosols, Clouds, Rainfall, and
Climate, 2002) dry-to-wet transition period. There was also a predominance of
particles in the accumulation mode during the biomass burning episodes of
LBA-CLAIRE (Cooperative LBA Airborne Regional Experiment, 2001)
, although particle number concentrations were lower for
these periods. Finally, the last case is a highly polluted case (HP5,5)
(Fig. c) with 5000 cm-3 in both modes, resembling
the observed distribution during the SMOCC dry period ,
minus the nucleation mode. Particles in the nucleation mode are not expected
to impact significantly the CCN behavior of the aerosol population and were
disregarded.
In both CLAIRE and SMOCC experiments, smoke particles were found to be
externally mixed in terms of hygroscopicity .
The less hygroscopic group presented very low hygroscopicity
κp values, between 0.032 and 0.068, while the
κp values for the more hygroscopic group were low, ranging
between 0.110 and 0.172 (Table S2 of
Supplement). Here, the following classification by was
considered: very low hygroscopicity (VLH, κp<0.1), low
hygroscopicity (LH, 0.1≤κp<0.2), medium hygroscopicity
(MH, 0.2≤κp<0.4) and high hygroscopicity (HH,
κp≥0.4). Neither set of observations included smoke
particles with κp>0.2. The hygroscopic group number
fractions varied, with very low hygroscopicity particles accounting for
20 % of the total number concentration , or up to
85 % (Table S2). As a result, the population
effective hygroscopicity parameter κpeff ranged
between 0.05 and 0.13.
Schematic number size distributions for MP5,1 (a),
MP1,5 (b) and HP5,5 (c) case studies. Total
population (black, solid), Aitken (red, solid) and accumulation (blue, solid)
modes are indicated. Particles in hygroscopic group κp=0.04
(dashed line, all colors) are also shown for a population average
κpeff=0.10.
To assess the role of aerosol mixing state outside equilibrium conditions,
cloud model simulations were conducted for populations both externally and
internally mixed. The variability in the population effective
κpeff was simulated assuming that the population is
composed by two populations externally mixed in terms of hygroscopicity,
having κp=0.04 and κp=0.16, respectively,
with a resultant population effective hygroscopicity estimated as
κpeff=∑κphgfhg
that varies according to the number fraction fhg
of each hygroscopic group, hg (Table ). This case is denoted
Ext1. A second possibility, denoted Ext2, was considered to account
for more hygroscopic biomass burning aerosols observed for other
biomass/regions. In this second case, the κp of the more
hygroscopic group is increased from κp=0.16 to a medium
hygroscopicity value, κp=0.30, with a resultant population
effective hygroscopicity also varying according to the number fraction of
each hygroscopic group (Table ). Finally, the internally mixed
population was denoted Int. Results obtained for two hygroscopic groups of
particles externally mixed are compared with results obtained if the
population is assumed to be internally mixed. The minimum/maximum
κpeff in both sets of externally mixed populations
is reached for the extreme case when only one group is present (therefore
reducing to the internally mixed case) and is equal to the hygroscopicity
parameter of particles in this group.
Number fractions for the hygroscopic groups in the externally mixed
populations Ext1 and Ext2.
Ext1
Ext2
κpeff=
∑κphgfhg
fκp= 0.04
fκp= 0.16
fκp= 0.04
fκp= 0.30
0.04
1.00
0.00
1.00
0.00
0.06
0.83
0.17
0.92
0.08
0.08
0.67
0.33
0.85
0.15
0.10
0.50
0.50
0.77
0.23
0.12
0.33
0.67
0.69
0.31
0.14
0.17
0.83
0.62
0.38
0.16
0.00
1.00
0.54
0.46
0.18
–
–
0.46
0.54
0.20
–
–
0.38
0.62
0.25
–
–
0.19
0.81
0.30
–
–
0.00
1.00
The effective κpeff and the corresponding fractions
of each group for both situations and different fractions of the hygroscopic
groups are presented in Table . The schematic size distribution
of the aerosol total population and that of the hygroscopic group with
κp=0.04 are indicated in Fig. 1 for the three case studies,
for a κpeff=0.10 and Ext2 external mixing
state. The aerosol composition was considered to be independent of particle
size, assuming that the slight tendency of higher hygroscopicity of larger
particles (Table S2) was typically not large enough to impact significantly
the CCN behavior of the population. Simulations were conducted for the
internally mixed population (Int) with hygroscopicities that ranged from
κp=0.02 to κp=0.60, for the defined
MP5,1, MP1,5 and HP5,5 cases, in order to analyze the effect
of hygroscopicity. Simulations conducted for the externally mixed population
(Ext1 and Ext2) ranged between the minimum and maximum
κpeff (0.04 to 0.16 and 0.04 to 0.30, respectively).
Updraft velocities between 0.1 and 10 ms-1 were considered.
Higher number concentrations than considered here can be found in
pyrocumulus, but it is probably safe to assume that their impact on the
hydrological cycle and aerosol indirect effect on a regional scale is
secondary when compared with that of the regional haze, so these extreme
cases of polluted conditions were not covered in our study. According to the
regimes proposed by , our study focused largely on the
aerosol-limited and aerosol- and updraft-sensitive regimes, with particle
number concentrations that characterize polluted conditions like those found
in the regional haze. For MP5,1 and MP1,5 cases, the updraft-limited case is given approximately by W≤1 ms-1, but the
aerosol-limited is given by W≥6 ms-1. For the HP5,5
case, the approximate limit of the updraft-limited case is given by W≤1 ms-1, and the aerosol-limited by W≥10 ms-1 (not considered in our simulations).
Cloud-base initial conditions for the simulations were temperature of
293 K, atmospheric pressure of 900 hPa and relative humidity
of 98 %. Sensitivity tests indicated only a weak dependence (absolute
differences between maximum supersaturations obtained initializing at 80 and
at 99 % below 0.03 %) of maximum supersaturations with the initial
relative humidity for the highest updraft values, and a negligible effect in
the activated fraction (see Fig. S1 of the Supplement). To avoid unrealistic physical
parameters, the final time of simulation was defined somewhat arbitrarily as
the time required for the parcel to ascend 500 m at the considered
updraft velocity. The parameters for the simulations are summarized in
Table . The distribution was discretized into 1000 bins ranged
from 15 to 104 nm, leading to a relative error of less than
0.003 % with respect to the lognormal distribution for all the cases
considered in this study. To exclude particles that are not large enough to
activate, only particles larger than 30 nm (Na,30) were
considered as aerosol number concentrations in the calculation of
Nd/Na fractions. For all the cases considered, the cloud
nuclei larger than 30 nm fraction included almost all particles, with
the lowest fraction Na,total/Na,30=0.994 obtained for
case MP5,1.
Parameters for the simulations.
Parameter
Value/range
Updraft velocity
0.1–10 ms-1
Hygroscopicity parameter
Int
0.02–0.60
Ext1
0.04–0.16
Ext2
0.04–0.30
Initial conditions
Relative humidity
98 %
Temperature
293 K
Atmospheric pressure
900 hPa
Air parcel height
500 m
Results and discussion
Maximum values of supersaturation and CCN activated fraction, as a function of
hygroscopicity, updraft velocity and mixing state, are presented in
Fig. for the various proposed case studies and mixing states.
Due to the high particle number concentrations that characterize polluted
conditions in the three case studies, maximum supersaturations reached in the
simulations were typically low and, except for the highest updraft velocities
and for very low hygroscopicity values (VLH, κp<0.1), had
values below 0.5 % in the MP5,1 case and below 0.4 %
in the MP1,5 and HP5,5 cases. The highest values of maximum
supersaturation were obtained for the MP5,1 case, with the majority of
particles in the Aitken mode. Maximum supersaturations in this case were, on
average, ∼ 0.10 % larger (absolute differences) than those obtained
for MP1,5 case, and about 0.15 % higher than those obtained for
HP5,5 case. Meanwhile, the values of maximum supersaturation reached in
the MP1,5 case study were higher than those obtained in the HP5,5
case, but slightly higher, with absolute differences between maximum supersaturation
values of up to 0.05 %, all else being equal, in spite of the much higher
particle number concentrations in the latter case. The case study with the
highest Na, HP5,5, presented the largest cloud droplet number
concentrations. However, the largest Nd/Na fractions were
instead reached in the MP1,5 case, all else being equal. The activated
fractions for the HP5,5 case were the lowest between all three cases for
all values of κp within the low hygroscopicity (LH, 0.1≤κp<0.2) and medium hygroscopicity (MH, 0.2≤κp<0.4) ranges, while for κp in the VLH range
the lowest Nd/Na fractions were obtained for the MP5,1
case.
Maximum supersaturation reached (top) and fraction of particles
activated (bottom) for the internal mixing (solid line) and external mixing
cases Ext1 (dotted line) and Ext2 (dashed line). Plots on
columns (a, d), (b, e) and (c, e) are for
MP5,1, MP1,5 and HP5,5 case studies, respectively. The color
scale refers to the updraft velocities from 0.1 to 10 ms-1.
These results for the maximum supersaturations and Nd/Na
fractions are explained by the Köhler theory, which predicts that the
Kelvin term typically dominates the growing process for larger particles,
while the Raoult term is more relevant for smaller ones. Therefore, particles
in the accumulation mode are likely to condense water vapor on their surfaces
more readily than the comparatively smaller particles in the Aitken mode,
growing larger and impacting the maximum supersaturation reached more than
the latter. Moreover, the Raoult term is more significant the smaller the
particle; thus, the activation of particles in the Aitken mode is expected to
be more altered by hygroscopicity than the activation of particles in the
accumulation mode.
Among the variable parameters within the simulations, both maximum
supersaturations and Nd/Na fractions were impacted the most
by updraft velocity, for all study cases and mixing states. Mean
sensitivities of Nd to W in the MP5,1, MP1,5 and
HP5,5 study cases were 0.66, 0.65 and 0.73, respectively, with very
little variability with mixing state, as illustrated in Fig.
for κpeff=0.10. These mean values of SW are
higher than previous estimations of 0.18 and 0.47 for clean
(< 1000 cm-3) and polluted (1000–3000 cm-3)
conditions, respectively, by . However, an increase in the
sensitivity to W with the number concentration is consistent with the
behavior expected within the updraft- and aerosol-sensitive regime that is,
on average, the predominating regime. The adjusted R2 coefficients in the
linear fits of the lnNd vs. lnW curves were ≥ 0.90 for
all cases and mixing states. However, the data points departed from the mean
slope towards low and high updraft velocities for all case studies and mixing
states (Fig. , top). Cloud droplet number concentrations were
more sensitive (local SW up to 0.9) to increases in the updraft velocity
for velocities within the updraft-limited regime, while for the
aerosol-limited regime the sensitivity to W decreased to values between 0.1
and 0.4 (Fig. , bottom). This varying sensitivity of
Nd to W is in agreement with the changing behavior within each
regime of CCN activation described by , which varies from a
high sensitivity of activation with W in the updraft-limited regime to
almost no influence in the aerosol-limited one. The sensitivity of
Nd to the aerosol number concentrations and the geometric mean
diameter and standard deviation have been discussed elsewhere
and was not addressed here.
Number of particles activated (top) and sensitivity SW of
Nd to the updraft velocity W (bottom) for
κpeff=0.10, obtained for the MP5,1 (solid
line), MP1,5 (dashed line) and HP5,5 (dotted line) case studies.
Results for internal mixed Int population and externally mixed populations
Ext1 and Ext2 are in black, red and blue, respectively.
Schematic number size distribution of particles activated in Ext2
(hatched area) and Int (grey area) mixing states, for an average
κpeff=0.10 and W=5 ms-1, for
(a) MP5,1, (b) MP1,5 and (c) HP5,5
case studies. Total aerosol population (black, solid line), hygroscopic group
κp=0.04 (black, dashed line) and maximum supersaturation
reached in the simulations for each mixing state are indicated.
In contrast with SW, the sensitivity to hygroscopicity
Sκp changed substantially with mixing state; this will be
discussed in Sect. 4.2.
Aerosol mixing state
The aerosol mixing state modified both maximum supersaturations and activated
fractions, although to different extents. The values of maximum
supersaturation were slightly underestimated for updraft velocities in the
aerosol-limited and the aerosol- and updraft-sensitive regimes when internal
mixing was assumed (Fig. , top). The absolute differences were
up to ∼ 0.01 and ∼ 0.03 % for the externally mixed Ext1
and Ext2 populations, respectively. For updraft velocities within the
updraft-limited regime, however, the maximum supersaturation reached were
lowest, and the values assuming an internal mixing were almost identical or
marginally higher than those reached for externally mixed populations.
On the other hand, the internal mixing hypothesis typically led to
overestimations of Nd, regardless of the somewhat lower values of
maximum supersaturation reached for this mixing case. The effect of
hygroscopic mixing state in the CCN activation behavior of aerosols can be
illustrated through the consideration of an aerosol population with known
size and composition but no information on the mixing state. Particles in the
externally mixed population will have either larger or smaller hygroscopicity
parameters than that of the internally mixed population average. The more
hygroscopic groups in the external mixture will have smaller cut particle
diameters and will activate more readily than the internally mixed particles.
Consequently, if internal mixing is presumed, the number of more hygroscopic
particles that become cloud droplets would be underestimated.
Overestimation of Nd when the aerosol is assumed
internally mixed, calculated as a function of the hygroscopicity (color
scale) and the updraft velocity, for the external mixing Ext1 (left) and
Ext2 (right). Plots on panels (a, b), (c, d)
and (e, f) correspond to MP5,1, MP1,5 and HP5,5 case
studies, respectively. Box plots on top of data represent the spread for
different hygroscopicity parameters. The box boundaries delimitate the
interquartile range and mean values are indicated by diamond symbols. Dashed
lines represent the approximate boundaries between CCN activation regimes.
Although differences in activation for more and less hygroscopic particles
due to internal mixing will contribute with opposite signs to the total
Nd derived from mixing state, they are unlikely to cancel each
other out. In a simulation selected to illustrate the impact of mixing state in
Nd, an externally mixed population (Ext2) has one hygroscopic
group with κp=0.04, in the VLH range, present in a fraction
fκp= 0.04=0.77, and a second hygroscopic group with
κp=0.30, within the MH range, with fκp= 0.30=0.23. Assuming internal mixing (Int), these two groups resulted in
κpeff=0.10 (Table ). For this specific
case, the schematic size distribution of particles that are activated as CCN
in the MP5,1, MP1,5 and HP5,5 case studies at a prescribed
updraft velocity of W=5 ms-1 are presented for external and
internal mixtures in Fig. 4. The values of maximum supersaturations reached
were somewhat lower when internal mixing state was assumed, between 2 and
3 % depending on the study case. A fraction of particles in the MH
hygroscopic group (κp=0.30) was indeed activated as CCN in
the externally mixed Ext2 but was not in the internal mixing, since the
internally mixed population κpeff is lower and thus
the cut size for activation in the internally mixed population is larger.
However, an even larger fraction of the particles in the VLH group were not
activated in the external mixing, but these were considered as activated when
an internal mixing state was assumed. Thus, in this example, and
characteristically in the conducted simulations, assuming internal mixing for
an externally mixed population led to an overestimation of Nd.
Box plots on top of data in Fig. display the magnitude of the
overestimation in Nd if internal mixing is assumed for an
externally mixed population, for the range of updraft velocities and
κpeff. The overestimation of Nd was
expressed as Nd,Int/Nd,Ext-1, where
Nd,Int and Nd,Ext refer to estimations for
internally and externally mixed populations, respectively, and the population
is considered to be externally mixed. Overestimations of Nd when
assuming internal mixing were larger when the module of the difference
between the internal mixture κpeff and that of the
hygroscopic group with closest value of hygroscopicity in the external
mixture was greater, i.e., when the internally mixed assumption was
comparatively less valid. Overestimations close to the lower limit or below
the interquartile range of CCN overestimations were obtained for populations
with fractions fκp= 0.16≥0.67 in the Ext1 (with a
resulting κpeff≥0.12), and
fκp= 0.30≥0.62 in the Ext2 mixing
(κpeff≥0.2). Within the aerosol- and
updraft-sensitive regime, the overestimations of Nd were largest
for all three cases. The higher number concentration of particles in the
Aitken mode in the MP5,1 and HP5,5 case studies resulted in larger
overestimations in the CCN number concentrations even for the upper range of
updraft velocities. In contrast, the overestimations of Nd
decreased noticeably as the updraft velocity increased towards the
aerosol-limited regime for the MP1,5 case. Within the updraft-limited
regime the typically low fractions of activated particles, as well as the
estimations of Nd,Int/Nd,Ext-1, were more susceptible
to inaccuracies due to bin resolution.
Average overestimations of Nd for the externally mixed population
Ext1 were typically low, 5.7 ± 2.4, 5.1 ± 2.1 and
2.9 ± 2.0 %, or the MP5,1, MP1,5 and HP5,5 case
studies. For population Ext2, and the same case studies, averages were
slightly higher, 12.4 ± 4.7, 10.4 ± 4.5 and
10.5 ± 3.8 %, respectively. However, with particle number
concentrations of 10 000 cm-3 in the HP5,5 case and
6000 cm-3 in the MP5,1 and MP1,5 case studies,
the absolute overestimations
(Nd,Int-Nd,Ext) in the CCN number concentration for
these cases were, respectively, 160 ± 94, 181 ± 96 and
224 ± 137 cm-3 for Ext1 simulations and 349 ± 203,
358 ± 188 and 467 ± 272 cm-3 for Ext2. Maximum
absolute overestimations were reached for higher updrafts, for which the
Nd/Na fraction was higher for all mixing states. For
Ext1 simulations, the maximum absolute overestimations were 304, 323 and
432 cm-3 for the MP5,1, MP1,5 and HP5,5 cases,
respectively, while in Ext2 simulations for the same study cases they were
of 637, 642 and 838 cm-3. The high aerosol number concentrations
considered here, although characterizing polluted conditions like those that
could be found in regional hazes in the Amazonia region, are still moderate
in comparison with concentrations inside pyrocumulus.
It is important to note that, were the maximum supersaturations achieved in
simulations for both mixing states to be the same, Nd would be higher in the
internal mixing case simulations and the CCN overestimations derived from
assuming internal mixing would be larger. This difference in the achieved
maximum supersaturations does not explain the much smaller impact of mixing
state found for cloud parcel model results when compared to those obtained
for equilibrium conditions and prescribed supersaturations, but is likely to
contribute to it since, in the latter, the same maximum supersaturation is
assumed in the estimation of Nd for the different mixing states.
For Amazon smoke particles, these results indicate an overestimation in Nd
derived from assuming internal mixing overestimation for an externally mixed
population that is below 10 % for all conditions.
Hygroscopicity
The behavior of the CCN activation, as hygroscopicity changed, was distinctly
different for the different mixing states. When the population was assumed to
be internally mixed, the mean average sensitivity to hygroscopicity,
Sκp, was low for the case MP5,1 (0.20), and very low
for MP1,5 (0.10) and HP5,5 (0.12) case studies. These estimations
are in good agreement with those by and .
For the externally mixed population, however, ln-ln curves were far
apart from a linear behavior and it was not possible to achieve linear fits.
Obtained adjusted R2 parameters were close to zero or negative and hence
average sensitivities for externally mixed populations were not estimated.
Local sensitivities for the internal mixing state typically decreased as the
hygroscopicity parameter increased, starting from median values of
∼ 0.35 for the MP5,1 case study and of ∼ 0.20 for the
MP1,5 and HP5,5 case studies (Fig. ) until almost
stabilizing at values close to 0.15, 0.05 and 0.10 for the same cases for
values of κp within the medium and high hygroscopicity ranges.
Notable exceptions were found within the updraft-limited regime for
populations with high hygroscopicity where the impact of kinetic effects was
high, as will be addressed later in Sect. 4.3. Except for cases within the
updraft-limited regime, where kinetic limitations were significant, we found
that the impact of the hygroscopicity parameter in Nd was very low
for internally mixed populations and κp within the MH or the
HH ranges, while for κp values within the VLH range the impact
was low to moderate, in agreement with results obtained by previous studies
.
Box-and-whisker plots of the sensitivity Sκp of
Nd to the hygroscopicity parameter κp, showing
spread of results for updraft velocities between 0.1 and
10 ms-1, for (a) MP5,1, (b) MP1,5
and (c) HP5,5 case studies. Box bounds show the interquartile
range, the mean value is indicated by a small square, and whiskers delimitate
minimum and maximum values. Results for the internally mixed Int and
externally mixed populations Ext1 and Ext2 are plotted in black, red
and blue, respectively.
On the other hand, the local Sκpeff for the
externally mixed populations presented mean values (over results for
different updraft velocities) that increased with
κpeff from very low or even negative to values
between 0.3 and 0.45 for the highest κpeff values
(Fig. ). This higher sensitivity of Nd to
κpeff in the external mixtures is also apparent in
the step increase in Nd obtained for the external mixing results
for the larger average κpeff values
(Fig. , bottom).
The increasing Sκpeff for external mixing cases
can be illustrated through the consideration of the following example for the
HP5,5 case and an updraft velocity W=5 ms-1. In the
internally mixed population with κp=0.30, 62 % of the
total Nd was activated. If the internally mixed population has,
instead, κp=0.25, the resulting Nd/Na
fraction is ∼ 61 %. However, if the population with
κpeff=0.25 is instead externally mixed, the
fraction of particles with κp=0.30 that reached activation
increased to 67 %, but, of the particles with κp=0.04
(19 % of total population), only 22 % reached activation.
Consequently, even when the MH particles predominated, the resulting ratio
was 58 %, a more significant decrease from the case with κp=0.30 than in the internally mixed population case.
Considering the results from the simulations and the little variability and
low values of Sκpeff for internally mixed
populations, variations in hygroscopicity within the MH and HR could be
considered instead as secondary and neglected, especially if the difference in
hygroscopicity is not large, since the level of sophistication within GCMs
should be kept at a minimum whenever the accuracy of results is not
compromised. When the hygroscopicity is within the LH and VLH, however, the
overestimation in the activated fraction might also be substantial, as illustrated
in Fig. for updraft velocities in the updraft- and aerosol-sensitive regime, for internally mixed populations. In the extreme case
when κp=0.20 was assumed for a population of
κp=0.04, the mean overestimation of the CCN population for
the MP5,1, MP1,5 and HP5,5 was
54.3 ± 3.7, 22.4 ± 1.4 and 26.6 ± 2,3 %, respectively. In
comparison, if κp=0.60 was presumed for aerosols with
κp=0.20, the mean overestimations of Nd obtained
for the MP5,1, MP1,5 and HP5,5 cases and the same range of
updraft velocities were 15.5 ± 1.6, 4.8 ± 0.3 and
6.4 ± 0.8 %, respectively.
Overestimation of Nd (mean ± standard deviation over
the updraft velocities in the updraft- and aerosol-sensitive regime) when
κp=0.20 is assumed, as a function of the population
κp. Results correspond to MP5,1 (blue), MP1,5
(orange) and HP5,5 (grey) case studies for an internally mixed
population.
A significant overestimation of Nd can thus result from assuming a
hygroscopicity in the MH range for the Amazon smoke aerosols. These results
suggest that larger values of κp like those recommended for
continental aerosol or biomass burning particles in other regions of the
world are not adequate to describe the CCN activation behavior of Amazon
smoke particles.
Kinetic limitations
Temporal series of the CCN activation with resolutions of 0.5 and 1 s near
the time of maximum supersaturation for strong and low to moderate updrafts,
respectively, were used to analyze the particle growth and activation
evolution in time. Three separate effects in the evolution of Nd
were observed in the simulations for weak and sometimes even moderate
updrafts that could be attributed to the effect of kinetic limitations: (1) a
delay between the time when maximum supersaturation was reached and the time
when the activated fraction is largest; (2) a decrease in the number of
activated particles with cloud depth after the maximum activated fraction is
reached; and, finally, (3) a overestimation of Nd if assuming that
equilibrium applies.
Supersaturation (left) and aerosol activated fraction (right) as a
function of cloud height for an internally mixed population with
κp=0.06 (black), κp=0.25 (red) and
κp=0.60 (blue), and W=0.5 ms-1. The cloud
droplet concentration was estimated as either Nd,eq (dashed line),
Nd,neqsimp (solid line, open circles) or
Nd,neq (solid line, close squares). The fraction of the population
not strictly activated in Nd,neq is indicated (open downward-facing
triangles). Plots on panels (a, b), (c, d)
and (e, f) correspond to MP5,1, MP1,5 and HP5,5 case
studies, respectively.
The delay in activation was amplified with the increase in the particle
κpeff. A relation to particle size and number
concentration was also apparent, being the delay longest for the HP5,5
case, moderate in the MP1,5 case, and much shorter for the MP5,1
case, also for large κpeff values and weak updrafts.
This is illustrated in Fig. for an internally mixed population
and W=0.5 ms-1. Due to the delay in activation a
significant fraction of particles was typically not activated at the time maximum
supersaturation was reached. Within the updraft-limited regime, the delay in
the activation was such that at the time of maximum supersaturation no
particles are activated for internally mixed populations with
κpeff above a certain threshold. For an updraft
velocity of =0.5 ms-1, this threshold was
κpeff=0.50 for the MP5,1 case and
κpeff=0.35 for the MP1,5 and HP5,5 cases. In the MP1,5 case, for an updraft velocity W=3 ms-1, already in the updraft- and aerosol-sensitive regime,
the threshold was still κpeff=0.35. The maximum
value of Nd,neqsimp was also reached sometime
after the maximum supersaturation is reached, and its value was slightly
higher than the maximum of Nd,neq. However, the strong kinetic
effects obtained for the larger κpeff values near
the time of maximum supersaturation for Nd,neq were not as strong
for Nd,neqsimp. After the maximum Nd,neq
is reached, however, differences between both estimations are below 1 %
and at the end of the simulation both estimations are very similar. The
fraction of particles not strictly activated in Nd,neq was
important only near the time of maximum supersaturation, indicating that this
assumption has no influence in results presented in previous sections, where
cloud droplet concentrations were estimated at the end of the simulation.
However, the differences near the time of maximum supersaturation would be
larger if this fraction is disregarded.
For the externally mixed population Ext1, although Nd,neq was
significantly lower than Nd,eq for weak updrafts, in all the cases
at least a fraction of particles was activated at the time of maximum
supersaturation. For Ext2 and W=0.5 ms-1, however,
populations with κpeff≥0.12, or
fκp= 0.30≥0.31, also showed Nd,neq=0 for
both MP1,5 and HP5,5 cases at the time of maximum supersaturation.
This is exemplified in Fig. for three values of the
effective hygroscopicity parameter. Interestingly enough, particles from both
hygroscopic groups failed to activate in these conditions. The value of
maximum supersaturation was very low in these cases, and it is likely that
particles in the more hygroscopic group condense the limited water vapor on
their surfaces more readily, although not in great enough quantities as to activate
themselves, but limiting the water vapor available to less
hygroscopic particles even more and preventing their activation as well. Particles from
both groups seem to grow rather slowly, and both groups appear to activate at
the same time.
Supersaturation (left axis, grey) and aerosol activated fraction
during the simulation (right axis) for the Ext2 population and the
HP5,5 case study, for W=0.5 ms-1 and
κpeff=0.06 (a),
κpeff=0.14 (b) and
κpeff=0.25 (c). The cloud droplet
concentration was estimated as Nd,eq (dashed line), and
Nd,neq for the population (black solid line, close squares) and
hygroscopic groups with κp=0.04 (red dashed line, open
circles) and κp=0.30 (blue dotted line, open upward-facing triangles).
As moderate and strong updrafts were considered, the delay between maximum
supersaturation and maximum activation reduced until no longer observed at
the temporal resolution of the time series. Within the updraft-limited
regime, the mean overestimation of Nd,neq in comparison with
Nd,eq over the range of κpeff, excluding
those that led to Nd,neq=0, ranged from ∼ 10 to
∼ 100 % in internally mixed populations, and between ∼ 10 and
∼ 250 % in externally mixed ones (Fig. ), being
larger for the higher values of κpeff. However, for
all case studies and mixing states, the overestimation at the time of maximum
supersaturation was typically below 12 % within the updraft- and
aerosol-sensitive, and below 5 % within the aerosol-limited regime.
Overestimation of Nd when the population is estimated
assuming equilibrium at the time of maximum supersaturation,
max(Nd,eq), compared with Nd,neq at the time of maximum
supersaturation (blue) and at the end of the simulation (orange), for the
range of updraft velocities. Values correspond to the
MP5,1 (a–c), MP1,5 (d–f) and
HP5,5 (g–i) case studies. The mixture of the aerosol
population was either internal (left panels) or external as in Ext1
(middle panels) and Ext2 (right panels)
The overestimation of Nd,neq at the time of maximum supersaturation
if assuming equilibrium applies can be explained by the evaporation
mechanism. However, as the cloud depth increases, and in particular at the
defined end of the simulation, the deactivation mechanism can be more
relevant. Although Nd,neq was always lower at the end of the
simulation than at its maximum, the difference was typically low, between 2
and 10 % for most updraft velocities and mixing states, as evidenced in
the similar overestimations of both values by max(Nd,eq). Both
evaporation and deactivation mechanisms were relevant for weak and even
moderate updrafts, and a relation with particle size and number concentration
was apparent, as previously reported by for ammonium
sulfate particles. Our results are also consistent with the reduction in the
droplet concentrations of up to 35 % due to kinetic limitations found by
for updrafts of 0.1 ms-1 and aerosol data
corresponding to the dry season in Amazonia.
In our results, the effects of kinetic limitations were strong when a
significant fraction of particles with hygroscopicity in the MH or LH range
was present. However, for particles with low and very low hygroscopicities
like the Amazon smoke particles, kinetic limitations were less important,
even if large aerosol loads were present.
A relation between the timescale of solubility and the CCN activation
behavior of aerosols is known , and several studies have
analyzed kinetic limitations by comparing the aerosol particles' growth and
that of a calibration aerosol with a high solubility and the same critical
supersaturation, with mixed conclusions regarding the importance of this
process to CCN activation
.
However, at the low supersaturations reached as a result of the weak updraft
velocity and the large aerosol loads considered, the kinetic limitations
discussed in this study derive more likely from the differences in water
uptake and critical supersaturation due to the particle hygroscopicity.
Conclusions
The available data on smoke particles in the Amazon region (Sect. 3) suggest
that this aerosol population has a rather consistent size and that
external mixing of two particle groups having very low and low
hygroscopicity, respectively, is typical for this aerosol population. We
conducted cloud model simulations using three hypothetical case studies and a
variety of hygroscopicities and mixing states that resembled typical
conditions found in the literature for smoke aerosols in the Amazon in
moderate to highly polluted conditions. Simulations were conducted for these
three case studies to estimate the effect of different values of
hygroscopicity and mixing state, including those conditions that resemble
observed data for smoke particles (Ext1). The impact of kinetic
limitations was assessed.
The impact in the surface tension due to the organic material present in
smoke aerosols is likely to be relevant , but
was not included in this work due to the complex organic composition of these
particles that lead to difficulties for its modeling. We consider this a limitation of our results that should be addressed in future works.
A low sensitivity of the cloud droplet number concentration Nd to
the population effective hygroscopicity parameter
κpeff was found for medium and large hygroscopicity
when the population was internally mixed. However, for particles with
hygroscopicity in the lower range of κpeff(<0.20),
the effective hygroscopicity of smoke particles for the Amazon appears to
stand in the VLH and LH ranges, where the sensitivity to this parameter was
found to be moderate. Therefore, Nd could be overestimated
significantly if larger values of hygroscopicity, like those suggested for
biomass burning particles elsewhere, were to be used for Amazonia smoke
particles.
Hygroscopic mixing state in the conducted cloud model simulations led to
differences lower than those obtained in previous studies that addressed
mixing state for equilibrium conditions and prescribed supersaturations. In
particular, the overestimation of Nd was low for populations
similar in hygroscopicity to the Amazon smoke aerosols (Ext1 in the
simulations), but slightly higher when the external mixing was between groups
with VLH and MH (Ext2).
The parameter κpeff posed a much larger impact on the CCN
activation within the MH range for externally mixed populations than for
internally mixed ones, even for low fractions of VLH aerosols. When
κpeff is estimated assuming internal mixing, and in particular
when particles of VLH are present, it is important to take into account that
the typically low sensitivity to hygroscopicity of internally mixed
populations does not apply and even relatively small variabilities in
κpeff could affect the CCN activation behavior of the
population. Consequently, assuming internal mixing of particles with very low
and low-hygroscopicity particles with moderate or large hygroscopicity should
be avoided.
Finally, kinetic limitations were found to be much lower for particles within
VLH and LH hygroscopic groups, and therefore its impact on the CCN behavior
of Amazon smoke particles is expected to be limited, in spite of the presence
of large aerosol loads.
The inclusion of mixing state, adequate hygroscopicity values and the
consideration of kinetic limitations into global and regional circulation
model are all possible, although in many cases at a computational cost. The
choice of using two separate aerosol populations to account for the
externally mixing character of the biomass burning population will increase
the computational burden of the model, and the modeler might choose instead
to consider biomass burning aerosols as only one population internally mixed
and externally mixed with other aerosol populations, given that the
overestimation derived from this choice is not significant. Global models or
regional models over a large domain should specify, if possible, the aerosol
hygroscopicity for different regions, in particular when values in the very
low or low range of hygroscopicity are to be considered. Also, for Amazonia
smoke aerosols, the choice of a parameterization that accounts for kinetic
limitations, typically more demanding in terms of computational resources,
might not improve results significantly over a parameterization that does not
account for their impact.