Measurements at high-Arctic sites (Alert, Nunavut, and Mt. Zeppelin, Svalbard) during the years 2011 to 2013 show a strong and similar annual cycle in aerosol number and size distributions. Each year at both sites, the number of aerosols with diameters larger than 20 nm exhibits a minimum in October and two maxima, one in spring associated with a dominant accumulation mode (particles 100 to 500 nm in diameter) and a second in summer associated with a dominant Aitken mode (particles 20 to 100 nm in diameter). Seasonal-mean aerosol effective diameter from measurements ranges from about 180 in summer to 260 nm in winter. This study interprets these annual cycles with the GEOS-Chem-TOMAS global aerosol microphysics model. Important roles are documented for several processes (new-particle formation, coagulation scavenging in clouds, scavenging by precipitation, and transport) in controlling the annual cycle in Arctic aerosol number and size.
Our simulations suggest that coagulation scavenging of interstitial aerosols in clouds by aerosols that have activated to form cloud droplets strongly limits the total number of particles with diameters less than 200 nm throughout the year. We find that the minimum in total particle number in October can be explained by diminishing new-particle formation within the Arctic, limited transport of pollution from lower latitudes, and efficient wet removal. Our simulations indicate that the summertime-dominant Aitken mode is associated with efficient wet removal of accumulation-mode aerosols, which limits the condensation sink for condensable vapours. This in turn promotes new-particle formation and growth. The dominant accumulation mode during spring is associated with build up of transported pollution from outside the Arctic coupled with less-efficient wet-removal processes at colder temperatures. We recommend further attention to the key processes of new-particle formation, interstitial coagulation, and wet removal and their delicate interactions and balance in size-resolved aerosol simulations of the Arctic to reduce uncertainties in estimates of aerosol radiative effects on the Arctic climate.
The climate impact of aerosols strongly depends on aerosol number and size distributions (Haywood and Boucher, 2000; Lohmann and Feichter, 2005). These aerosol properties, in addition to chemical composition, contribute to aerosol effects on the Earth's climate. Aerosols influence the global climate directly through scattering and absorption of radiation (Charlson et al., 1992) and indirectly by modifying cloud properties (Twomey, 1974; Albrecht, 1989). Aerosols play an important role in the Arctic climate, and changing aerosol concentrations are believed to have contributed to the rapid Arctic warming observed over the past few decades (Shindell and Faluvegi, 2009). However, in the Arctic there are complex aerosol feedbacks and strong seasonal aerosol cycles that make study of aerosol–climate interactions particularly challenging in this remote region (Browse et al., 2012, 2014). To address a portion of this challenging puzzle, this study focuses on understanding the processes that control the Arctic aerosol number and size distributions over the entire annual cycle.
Observations at Arctic sites show a strong and similar annual cycle in aerosol number and size distributions (e.g. Ström et al., 2003; Leaitch et al., 2013; Tunved et al., 2013). In the high Arctic, at Mt. Zeppelin, Svalbard, and Alert, Nunavut, Canada, the observed annual cycle in aerosol number exhibits two maxima: one in March–April associated with dominance of accumulation-mode particles and one in July associated with smaller, Aitken-mode particles. The inter-seasonal transition from accumulation-mode-dominated springtime distributions to Aitken-mode-dominated summertime distributions has been observed not only at surface sites but also in the free troposphere (Engvall et al., 2008). This inter-seasonal transition from spring to summer has been extensively studied; evidence suggests control by changes in aerosol wet-removal efficiency, new-particle formation, and transport patterns (e.g. Korhonen et al., 2008; Garrett et al., 2010; Sharma et al., 2013). More-efficient wet removal in the midlatitudes and within the Arctic in late spring and summer inhibits transport of aged accumulation-mode aerosols into the Arctic. These summertime conditions favour new-particle formation (hereafter referred to as NPF) from precursor vapours within the Arctic boundary layer due to the low condensation sink for particle-precursor vapours on to existing aerosol surface area, and the low coagulation sink for newly formed, growing particles (Leaitch et al., 2013; Heintzenberg et al., 2015).
Korhonen et al. (2008) conducted a pioneering global aerosol model study to interpret the processes controlling the spring-to-summer transition in Arctic aerosol number and size observed from Svalbard and the shipboard campaigns of Heintzenberg et al. (2006). The focus of that study was limited to spring–summer and the transition between these seasons. In our study, we extend the temporal scope to consider the entire annual cycle and use observations from both Svalbard and Nunavut, about 1000 km apart. Over recent years, numerous studies have focused on the spring–summer transitions in aerosol mass abundance using observations and models to examine the role of transport and scavenging (Garrett et al., 2010, 2011; Browse et al., 2012; Di Pierro et al., 2013; Sharma et al., 2013; Stohl et al., 2013). However, there has been considerably less focus on Arctic aerosol number and size distributions. To our knowledge, ours is the first global modelling study to consider the complete annual cycle in Arctic aerosol number and size.
In this study, we examine aerosol number and size distributions over recent
years (2011–2013) at the Canadian high-Arctic measurement site at Alert,
Nunavut (82.5
While the importance of wet removal is well known (Korhonen et al., 2008;
Garrett et al., 2010; Browse et al., 2012), relatively less attention has
been given to coagulation of interstitial particles in clouds, which is
another sink process for aerosol number. We implemented a mechanism in
GEOS-Chem-TOMAS that represents coagulation between aerosols that have
activated to form cloud droplets and interstitial aerosols (defined as
particles within clouds but outside of cloud droplets). This mechanism
accounts for the
The following section describes the 2011–2013 high-Arctic measurements and gives an overview of the GEOS-Chem-TOMAS simulations conducted for this study. Section 3 examines the monthly and seasonal-mean in situ observations of aerosol number and size from scanning mobility particle sizer (SMPS) at Alert and differential mobility particle sizer (DMPS) at Mt. Zeppelin. The GEOS-Chem-TOMAS model is used to interpret the annual cycle of these measurements. We subsequently present the process rates that control the aerosol annual cycles in our simulations.
Measurements of particle size distributions at Alert have been ongoing since
March 2011 with the exception of a few technical interruptions. Sampling of
the ambient aerosol size distribution at Alert was conducted as described by
Leaitch et al. (2013). Briefly, the particles are sampled through stainless
steel tubing with a mean residence time for a particle from outside to its
measurement point of approximately 3 s. At the point of sampling, the
aerosol is at a temperature (
The Department of Environmental Science and Analytical Chemistry, Section for Atmospheric research (ACES), Stockholm University (SU), has monitored the sub-micron aerosol number size distribution at Mt. Zeppelin since 2000 with a DMPS. Today, this more-than-15-year continuous data set constitutes one of the longest unbroken aerosol number size distribution observation series in the Arctic.
During the 15 years of operation, the DMPS system has undergone a number of modernizations. Initially a single differential mobility analyzer (DMA) system was used covering a size range between roughly 20 and 600 nm. A major overhaul was performed during late 2010, and since then the set-up has remained unchanged, covering a size range of 5–800 nm. Thus, the data used in our study (2011–2013) come from the same instrument configuration.
This DMPS system utilizes a custom-built twin DMA set-up comprising one
Vienna-type medium DMA coupled to a TSI CPC 3772 covering sizes between
25–800 nm and a Vienna-type long DMA coupled with at TSI CPC 3772
effectively covering sizes between 5 and 60 nm. The size distributions from the
two systems are harmonized on a common size grid and then merged. Both
systems use a closed-loop set-up. The inlet hat is a whole air inlet according
to EUSAAR standard. In the current set-up, the inlet operates with a flow rate of
about 100 L min
In this study, we use the GEOS-Chem-TOMAS model, which couples the GEOS-Chem
global chemical transport model (
The TOMAS microphysics scheme tracks the number and mass of particles within
each of 15 dry size sections. The first 13 size sections are logarithmically
spaced, including aerosol dry diameters from approximately 3 nm to
1
For these simulations, NPF is treated according to the state-of-the-science
ternary H
Growth of simulated particles occurs by condensation of sulfuric acid and organic vapours, which we assume to be non-volatile. These vapours condense proportional to the Fuchs-corrected aerosol surface area distribution (Donahue et al., 2011; Pierce et al., 2011; Riipinen et al., 2011). Condensational growth is not a sink for aerosol number but does transfer aerosol number between size bins while increasing aerosol mass. Coagulation is an important sink for aerosol number (particularly for aerosols with diameters smaller than 100 nm) and moves aerosol mass to larger sizes. Our simulations use the Brownian coagulation scheme of Fuchs (1964) and consider coagulation between all particle sizes.
Summary of the simulations conducted for this study.
In our simulations, aerosols are removed from the atmosphere by precipitation
both in and below clouds (Liu et al., 2001) as well as by dry deposition using
a resistance in-series approach (Wesley, 1989) assuming an aerosol dry
deposition velocity of 0.03 cm s
Table 1 summarizes the four simulations conducted with the GEOS-Chem-TOMAS model. These simulations include (1) a standard, (2) updates to wet removal, (3) updates that add the process of interstitial coagulation of aerosols in clouds, and (4) a sensitivity test with no NPF. The first (simulation STD) uses the standard GEOS-Chem-TOMAS model as described above.
Simulation NEWSCAV introduces developments to the wet-removal
parameterization to allow for variable in-cloud water content, to implement a
temperature-dependent aerosol activation fraction, and to more closely relate
in-cloud aerosol scavenging to cloud fraction. The standard GEOS-Chem-TOMAS
wet-removal efficiency
In addition, we implement a temperature-dependent representation of the aerosol activated fraction (Verheggen et al., 2007) to account for the fraction of aerosol susceptible to wet removal in mixed-phase clouds. In mixed-phase clouds, only a fraction of the aerosols are contained in the cloud hydrometeors and susceptible to removal when cloud water and ice converts to precipitation. As clouds glaciate, cloud droplets evaporate and release aerosols from the condensed phase because ice crystals grow at the expense of cloud droplets due to differences in the saturation vapour pressure over liquid water and ice. The Verheggen et al. (2007) parameterization for activated fraction accounts for this effect, such that only a fraction of the total in-cloud aerosol is susceptible to wet removal as precipitation forms in mixed-phase clouds. However, in strongly riming-dominated regimes, this may lead to an underestimation of the removal.
We also develop the representation of the precipitation fraction. In the
standard GEOS-Chem model, the fraction of the grid box that is
precipitating,
Simulation NEWSCAV
Measured monthly median number distributions from the scanning mobility particle sizer (SMPS) at Alert for 2011–2013 and the differential mobility particle sizer (DMPS) at Mt. Zeppelin for 2011–2013 for particle sizes between 20 and 500 nm. Error bars show the 20–80th percentile of the measurements.
Simulation NONUC turns off NPF globally to examine the contribution of NPF to aerosol number in the Arctic. This simulation is otherwise identical to simulation NEWSCAV.
Figure 1 shows the 2011–2013 monthly median aerosol number distributions
from the SMPS at Alert and DMPS at Mt. Zeppelin. At both sites, the
accumulation mode (defined here as particles with diameters from 0.1 to
0.5
Figure 2 shows the monthly median aerosol effective diameter calculated from
the 2011–2013 measurements with SMPS at Alert and DMPS at Mt. Zeppelin. The
effective diameter is the ratio of the second and third moments of the
aerosol number distribution and is useful for determining the optical
properties of an aerosol distribution and for comparing between
distributions. The effective diameter is defined as
Measurement monthly median aerosol effective diameter from SMPS and DMPS at the two high-Arctic sites, Alert (2011–2013), and Mt. Zeppelin (2011–2013) respectively for particle sizes between 20 and 500 nm. Error bars show the 20th and 80th percentiles.
Seasonal-median number distributions from SMPS measurements at Alert (2011–2013) and for the GEOS-Chem-TOMAS dry size distribution simulations (described in Table 1). The measurement 20–80th percentile is in grey shading. Simulations are shown in colour as indicated by legend.
Figures 3 and 4 show the seasonal-median number distributions from
measurements at Alert and Mt. Zeppelin respectively for winter (DJF),
spring (MAM), summer (JJA), and autumn (SON) and also for our four
simulations. The measurement distributions exhibit the key features of Arctic
aerosol size distributions, a dominant Aitken mode in summer, a dominant
accumulation mode with suppressed Aitken mode in non-summer seasons, and
minimum number in autumn. To assist in interpreting Figs. 3 and 4, we calculate
the fractional bias between the observed and simulated total number of
aerosols over two size ranges available from the measurement data: (1) Aitken
particles 20–100 nm in diameter and (2) accumulation particles 100–500 nm
in diameter. We apply a size limit of 20–500 nm to the Mt. Zeppelin
measurement data and to our simulations to be consistent with the available
data from Alert. We define fractional bias (FB) as
The strong control of wet removal on Arctic aerosol number and size distributions throughout the annual cycle is highlighted by comparison of simulations STD and NEWSCAV in Figs. 3 and 4 and in Tables 2 and 3. For both Alert and Mt. Zeppelin, the standard GEOS-Chem-TOMAS model (simulation STD) overestimates the observed number of 100–500 nm diameter particles in all seasons as quantified by the positive fractional bias values in Tables 2 and 3. At both Alert and Mt. Zeppelin, this bias is reduced in spring and summer for simulation NEWSCAV relative to STD. The bias reduction is greatest in summer when aerosol wet removal by precipitation is more efficient within the Arctic boundary layer, and it strongly limits the accumulation-mode number at the surface sites. The efficiency of wet removal is parameterized to increase with temperature (from 238 to 273 K) in our simulations. In seasons other than summer, wet removal in the Arctic boundary layer is less efficient. However, wet removal outside the Arctic boundary layer continues to influence the number of accumulation-mode particles transported to the measurement sites. Over a limited size range (200–500 nm diameter particles) and in all seasons at both sites, NEWSCAV is a closer match to measurements than STD, but the difference between STD and NEWSCAV is very small at Alert in winter and spring.
Model–measurement fractional bias (Eq. 6) for total number of aerosols with diameters of 20–100 and 100–500 nm at Alert (in reference to Fig. 3). Bias values closest to zero for each season are highlighted in bold.
Model–measurement fractional bias (Eq. 6) for total number of aerosols with diameters of 20–100 and 100–500 nm at Mt. Zeppelin (in reference to Fig. 4). Bias values closest to zero for each season are highlighted in bold.
Wet removal also has feedbacks that particularly influence Aitken-mode and 100–200 nm diameter particle numbers indirectly through changes in NPF and subsequent particle growth to these sizes. Figures 3 and 4 show that at both sites and in all seasons, more vigorous wet removal in simulation NEWSCAV relative to STD yields more numerous Aitken-mode particles (although the springtime difference is very small) and, in autumn and winter, also more numerous 100–200 nm particles. A reduction in surface area of 200–500 nm aerosols by more vigorous wet removal (simulation NEWSCAV relative to STD) promotes NPF and particle growth. Other than in summer, this NPF occurs primarily outside the Arctic boundary layer and growth occurs during transport to the measurement sites. As a result of the increase in number of 20–200 nm particles in simulation NEWSCAV relative to STD, the accumulation-mode bias is greater for NEWSCAV in autumn and winter at both sites and the Aitken-mode bias is greater for NEWSCAV in autumn, winter, and spring at both sites (Tables 2 and 3).
Seasonal-median number distributions from DMPS measurements at Mt. Zeppelin (2011–2013) and for the GEOS-Chem-TOMAS dry size distribution simulations (described in Table 1). The measurement 20–80th percentile is in grey shading. Simulations are shown in colour as indicated by legend.
The balance of these processes of NPF, growth, and wet removal is a challenge
for Arctic simulations of number and size. In all seasons at both sites
(except for summer at Mt. Zeppelin), NEWSCAV strongly over estimates the
number of 20–40 nm diameter particles. Nonetheless, among the four
simulations NEWSCAV has the closest-to-zero bias for the 20–100 nm and
100–500 nm diameter particles at Mt. Zeppelin in summer. As well, at Alert,
the summertime Aitken-mode bias for simulation NEWSCAV is second smallest
(after NEWSCAV
Figures 3 and 4 demonstrate the importance of in-cloud coagulation
(NEWSCAV
Simulation NONUC was designed as a means to assess the relative contribution
of NPF processes to the Arctic aerosol size distributions. In our
simulations, NPF contributes most strongly to the number of particles smaller
than 200 nm. These contributions occur in all seasons as shown by the
differences between NEWSVAC and NONUC in Figs. 3 and 4. In the summertime,
NPF occurs within the Arctic boundary layer both in our simulations and in
observations (Chang et al., 2011; Leaitch et al., 2013; Allan et al., 2015).
At this time of year, the Arctic region has greater production of oxidants
such as OH and has greater dimethyl sulfide (DMS) emissions from the oceanic
biological activity, such that oxidation of DMS by OH produces sulfur
dioxide (SO
Figures 5 and 6 show the annual cycle of the monthly median total number of
particles with diameters between 20 and 500 nm (N20), 80 and 500 nm (N80), and
200 and 500 nm (N200) from simulations and from measurements at Alert and
Mt. Zeppelin. To assist with interpreting Figs. 5 and 6, Tables 4 and 5
contain the mean FB (MFB) and mean fractional error (MFE)
following Boylan and Russell (2006).
Figures 5 and 6 demonstrate the key features of the annual cycle of integrated Arctic aerosol number distributions. Measurements from both Alert and Mt. Zeppelin show a shallow maximum in the N20 in both spring and summer. The measurement N80 and N200 have a maximum in March–April at both sites. The minimum for the N20, N80, and N200 from measurements occurs near September–October at both sites. All four simulations capture the general trend of N80 and N200 being higher in spring than in autumn, but there are some notable mismatches discussed below.
Similar to our findings in examining the seasonal-mean size distributions
(Figs. 3 and 4), Figs. 5 and 6 show that the N200 is highly sensitive to the
wet-removal parameterization. Simulation STD overpredicts the N200 at both
Alert and Zeppelin as evidenced by the greatest magnitude of the N200 MFB and
MFE among the four simulations at both sites for simulation STD. Wet removal
revisions for simulation NEWSCAV reduce the N200 MFB and MFE towards 0,
whereas implementation of the new coagulation mechanism has a lesser effect
on these N200 biases. NONUC has the closest-to-zero MFB for N200 among the
four simulations at both Alert and Zeppelin and also the lowest MFE at Alert.
However, the MFE for the N200 is similar between NONUC and NEWSCAV
Monthly median number concentration for aerosols with diameters of 20–500 nm (N20), 80–500 nm (N80), and 200–500 nm (N200) and effective diameter from the 2011–2013 Alert SMPS measurements and for the four GEOS-Chem-TOMAS dry size distribution simulations described in Table 1. The measurement 20–80th percentile is in grey shading. Simulations are shown in colour as indicated by legend.
The N20 and N80 are sensitive to the wet-removal and coagulation schemes.
Tables 4 and 5 show that interstitial coagulation (NEWSCAV
Monthly median number concentration for aerosols with diameters of 20–500 nm (N20), 80–500 nm (N80), and 200–500 nm (N200) and effective diameter from the 2011-2013 Mt. Zeppelin DMPS measurements and for the four GEOS-Chem-TOMAS dry size distribution simulations described in Table 1. The measurement 20–80th percentile is in grey shading. Simulations are shown in colour as indicated by legend.
Model–measurement mean fractional bias and mean fractional error (Eqs. 7 and 8) for N20, N80, N200, and effective diameter at Alert (in reference to Fig. 5). Bias and error values closest to zero for each season are highlighted in bold.
Geographic distribution of the simulated pan-Arctic surface-layer
seasonal-mean dry effective diameter (nm) for the NEWSCAV
Figures 5 and 6 also show the annual cycle of aerosol effective diameter at
both Alert and Mt. Zeppelin for our simulations and from measurements. The
simulation NEWSCAV
The similarity in the annual cycle of effective diameter from measurements at
both Alert and Zeppelin suggests a cycle that occurs throughout the Arctic.
Figure 7 shows the seasonal-mean pan-Arctic geographic distribution of the
surface-layer effective diameter for the NEWSCAV
Figure 8 shows the monthly- and regional-mean process rates that control
aerosol number in four size ranges for the entire troposphere north of the
Arctic Circle (66
Model–measurement mean fractional bias and mean fractional error (Eqs. 7 and 8) for N20, N80, N200, and effective diameter at Mt. Zeppelin (in reference to Fig. 6). Bias and error values closest to zero for each season are highlighted in bold.
Monthly and Arctic mean aerosol number process rates for the entire
Arctic troposphere (north of 66
The number of aerosols smaller than 10 nm in diameter (nucleation-mode size)
is primarily controlled by NPF (particle formation, also termed nucleation),
coagulation, and transport. There are two maxima in the particle formation
rate shown in Fig. 8 (top-left panel), one in early spring (March), and one in
summer (July). In spring, simulated NPF occurs mainly in the free
troposphere, whereas in summer, NPF occurs also in the boundary layer. In the
summertime Arctic boundary layer, NPF is enhanced by the low aerosol surface
area due to efficient wet removal of accumulation-mode aerosols by episodic
rain and summer enhancements in sulfuric acid production rates (from
oxidation of DMS). The simulated early-spring NPF rate maximum for
nucleation-size particles is associated with NPF in the middle and upper
troposphere and as a result is not evident in the measurements at Alert and
Mt. Zeppelin. This simulated springtime maximum in NPF occurs because the
precursors for sulfuric acid (DMS, SO
The top-left panel of Fig. 8 shows that transport reaches a maximum during
winter, while NPF reaches a minimum such that the two are comparable sources
for the entire Arctic troposphere. Simulated NPF occurs in the dark Arctic
wintertime since the oxidant OH is produced through reaction of ozone and
volatile organic compounds, although the OH mixing ratios are 3-fold less
than in summer. As a result, sulfuric acid (a particle precursor vapour) can
be produced though oxidation by OH of DMS and sulfur dioxide (SO
Figure 9 shows aerosol number transport rates at different altitudes by
decomposing the rates from Fig. 8 into four altitude bands. Nucleation-mode
particles are mostly transported in the mid- to upper troposphere (at
altitudes between 4 and 10 km) where the coagulation sink is sufficiently
low that nucleation-mode particles can persist. At these altitudes and
particularly when the atmosphere has just been cleaned by a precipitation event,
if the Aitken- and accumulation-mode concentrations are low
(5–10 cm
Monthly and Arctic mean aerosol number tendency due to transport
within each of four vertical layers between (1) 0–1.5 km, (2) 1.5–4 km,
(3) 4–10 km, and (4) above 10 km for the simulation NEWSCAV
Figure 8 (top-right panel) indicates that several processes control the simulated Aitken-mode number in the Arctic troposphere. Northward transport is the dominant source process for the Arctic Aitken mode during all months of the year. This transport of simulated Aitken-mode aerosols occurs throughout the troposphere as shown in Fig. 9. Figure 8 shows that during the Arctic spring (March–April), when the total aerosol mass is greatest, condensational growth of existing aerosols makes a relatively greater contribution to the total source rates for Aitken-mode particles. This net enhancement in condensational growth includes condensational loss of Aitken-mode particles to accumulation-mode sizes such that the nucleation mode is a larger source of Aitken-mode particles than apparent in the figure. Simulated primary particle emissions within the Arctic have a relatively constant source rate for the Aitken mode throughout the year, quite similar in magnitude to the maximum condensational growth rate in March–April. Coagulation is the dominant sink for the Aitken mode with dry deposition accounting for the majority of the remaining sink. Simulated removal of the Aitken-mode number by wet deposition is a weaker sink than dry deposition because the smaller Aitken-mode aerosols have inefficient removal by activation scavenging (the process of aerosols acting as the seed for cloud-droplet and ice-crystal formation and subsequent removal during precipitation). Recent studies indicate that aerosols as small as 50–60 nm can activate in the clean Arctic summertime conditions (Leaitch et al., 2013, 2016) and we likely underestimate this removal in our simulations. Figure 8 does show an increase in wet removal as a sink for the Aitken mode in summer as this process becomes more efficient at warmer temperatures and aerosols larger than about 60 nm are removed by activation scavenging in our simulations.
For the accumulation-mode particle number simulation, Fig. 8 (bottom-left panel) indicates that the dominant sources are northward transport and condensational growth, which also includes production of sulfate by in-cloud oxidation. These two simulated source terms are roughly equal in magnitude in the Arctic throughout April to October. Northward transport of accumulation-mode aerosols persists in the simulation in all seasons, with a minimum in winter and an increase in March–April. Figure 9 shows that transport of accumulation size aerosol at altitudes between 1.5 and 4 km reaches a maximum in April, which would contribute to the well-known Arctic haze phenomena. Figure 9 also shows that the majority of simulated accumulation-mode number transport is below 1.5 km. This low-level transport is persistent though diminished throughout the summer, suggesting that the summertime cleanliness of the Arctic near-surface atmosphere relies heavily on the increased efficiency of the removal processes in the lower troposphere during the summer months. Indeed, Fig. 8 shows that wet removal is the dominant accumulation aerosol number sink process in all seasons, but it increases in magnitude and relative importance with respect to dry deposition in the summer, accounting for about 90 % of the total summertime sink rate. In winter, the relative simulated importance of dry deposition for accumulation aerosol number increases, although it remains below 25 % of the total sink rate.
Since wet removal has large effects on the accumulation aerosol number
associated with Arctic springtime pollution, we further examined its annual
cycle. Figure 10 shows the monthly- and regional-mean accumulation-mode
number lifetime with respect to wet removal for layers of the lower
troposphere. Longer lifetimes from December to March contribute to the build
up of the Arctic haze layer, particularly as this is combined with transport
of pollution into the Arctic during wintertime. The spring to summer
transition period is characterized by a rapid increase in the efficiency of
wet scavenging that contributes to removal of the Arctic haze in April–May.
Figure 10 shows about a 5-fold decrease in wet-removal lifetime in the Arctic
1.5–4 km layer from February to April. Simulated wet-removal lifetimes in
the Arctic boundary layer below 1.5 km reach a minimum in October, such that
when combined with diminishing new-particle formation as the sunsets and
limited transport yields the simulated total aerosol number minimum in the
autumn season, similar to that observed at Alert and Mt. Zeppelin. To put the
Arctic region in context, Fig. 10 also shows the lifetimes with respect to
wet removal for the region north of 50
Regional- and monthly-mean aerosol number lifetime with respect to
wet deposition for accumulation-mode aerosol
numbers (100
Figure 8 shows that the simulated coarse mode is controlled primarily by emissions, transport and wet deposition. In early spring (March–April), northward transport of coarse-mode aerosols (dust and sea-salt emissions) is not quite matched by the removal processes. The resultant residual (black line on Fig. 8) gives the net rate of either aerosol build-up or loss for the regional monthly mean number. In early spring, there is a net build-up of coarse-mode aerosol in the Arctic region. However as spring progresses, there is a net loss such that the net residual integrates to 0 over the annual cycle. Wet removal is the primary loss process in all seasons in this simulation. Figure 9 shows that the early-springtime transport of the coarse mode occurs mainly at altitudes between 1.5 and 4 km, a time when the polar dome still extends relatively far southward.
Monthly- and regional-mean aerosol number process rates for the
entire troposphere north of 50
In this section we examined process rates over the entire troposphere north
of 66
In this study, we examined the annual cycle of aerosol number and size distributions in the Arctic from measurements made during 2011–2013 by SMPS at Alert and by DMPS at Mt. Zeppelin. There was a strong and similar annual cycle in measurements of aerosol number and size at both sites despite their geographic separation of 1000 km. The annual cycle in the total number of aerosols larger than 20 nm had two maxima. The maximum in spring was dominated by accumulation-mode aerosols (particles 100 to 500 nm in diameter) and in summer was dominated by Aitken-mode aerosols (particles 20 to 100 nm in diameter). At both sites, total aerosol number reached a minimum in October. The annual cycle of aerosol effective diameter derived from measurements had an inter-seasonal range between 180 and 260 nm, with a minimum in the summer. These annual cycles were similar to those presented by Tunved et al. (2013) based on earlier data at Mt. Zeppelin between the years 2000 and 2010.
We interpreted these annual cycles in Arctic aerosol number and size with the GEOS-Chem-TOMAS aerosol microphysics model. Our simulations indicated a strong sensitivity of the annual cycle of Arctic aerosol number and size to several key processes: new-particle formation, interstitial coagulation scavenging in clouds, wet removal through precipitation, and transport.
Our GEOS-Chem-TOMAS simulations demonstrated that wet removal had a strong control on Arctic aerosol number distributions throughout the annual cycle, similar to the findings of earlier studies focused on spring–summer (Korhonen et al., 2008) and Arctic aerosol mass abundance (e.g. Garrett et al., 2010; Browse et al., 2012; Sharma et al., 2013). In our study, wet-removal updates were developed for the GEOS-Chem-TOMAS model that together increased the efficiency of wet removal. We replaced the global-constant cloud liquid water content with the values from GEOS-5 assimilated meteorology fields, updated the grid-box precipitation fraction, and implemented the Verheggen et al. (2007) temperature-dependent aerosol activation fraction to account for the fraction of aerosol assumed to be susceptible to wet removal in mixed-phase clouds. In our updated removal simulation, efficient wet removal in the Arctic summertime boundary layer strongly limited the accumulation-mode number despite an ongoing source through transport and condensational growth. The wet-removal updates reduced model–measurement bias (relative to the standard model) for the number of aerosols larger than 200 nm in all seasons at both Alert and Mt. Zeppelin (although the changes in winter and spring at Alert were relatively small).
More vigorous wet removal promoted NPF and growth in our simulations and contributed to a summertime-dominant Aitken mode since a reduction in the surface area of accumulation size aerosols (the condensation sink for sulfuric acid) influences the likelihood that sulfuric acid will participate in NPF as opposed to condensing on existing aerosols. Indeed, the more vigorous wet-removal scheme increased the simulated Aitken-mode number in all seasons at Alert and Mt. Zeppelin (although the springtime Aitken mode was relatively less sensitive to the changes made in our study). Outside of summer, NPF and growth occurred mostly outside the Arctic boundary layer. A sensitivity study with no NPF globally indicated that NPF strongly controls the number of particles with diameters smaller than 200 nm in all seasons in the Arctic, while particularly important in yielding the summertime Aitken-mode dominance.
From February to April, the simulated accumulation-mode wet-removal efficiency at altitudes of the springtime Arctic haze layer (between 1.5 and 4 km) increased by 5-fold, contributing to our simulation of the spring–summer transition from Aitken- to accumulated-mode dominated Arctic size distributions (e.g. Engvall et al., 2008; Korhonen et al., 2008). In the boundary layer, simulated wet-removal efficiency reached a maximum (lowest accumulation-mode aerosol number lifetime) in October. The observed total aerosol number minimum in October was reproduced in our simulations due to efficient wet removal combined with diminished boundary layer NPF due to lower sulfuric acid concentrations and limited transport.
We also found an important role for coagulation of interstitial aerosols in clouds with aerosols of larger size that have activated to form cloud droplets. There has been relatively less attention given to the importance of this process in controlling Arctic size distributions despite the Arctic being a region with widespread cloud cover in all seasons. Implementation of an interstitial coagulation mechanism in clouds in our simulations reduced the number of aerosols with diameters smaller than 200 nm in all seasons at both Alert and Mt. Zeppelin. In some seasons this reduction in the Aitken-mode number worsened model–measurement agreement, highlighting the delicate balance between the processes of coagulation, NPF, growth, and wet removal in control of the Arctic size distributions that is challenging to simulate. Our simulations tended to under predict the number of larger Aitken-mode aerosols (40–100 nm in diameter) in summer and this is the subject of ongoing investigation related to aerosol sources and growth.
The high sensitivity of aerosol number to interstitial coagulation in clouds suggests that size-resolved models should include this process. However, many present-day global models neglect this process, including previous versions of GEOS-Chem-TOMAS (D'Andrea et al., 2013; Pierce et al., 2013; Trivitayanurak et al., 2008), GISS-TOMAS (Adams and Seinfeld, 2002; Pierce and Adams, 2009), GLOMAP (Spracklen et al., 2005a, b, 2008; Mann et al., 2012), GLOMAP-Mode (Mann et al., 2010, 2012; L. A. Lee et al., 2013), GEOS-Chem-APM (Yu and Luo, 2009; Yu, 2011), and IMPACT (Herzog et al., 2004; Wang and Penner, 2009). To our knowledge, only a few models such as MIRAGE and ECHAM-HAM (Herzog et al., 2004; Ghan et al., 2006; Hoose et al., 2008) represent this process.
Our results highlight the importance of aerosol processes (as well as their delicate balance and interactions) that continue to be poorly understood: (1) NPF and growth, (2) in-cloud interstitial coagulation, and (3) wet removal play a key role in the control of the annual cycle of aerosol number and size in the Arctic. The relative importance of the processes that control aerosol number could change in a future warming Arctic climate and also as emissions within the Arctic change.
The authors acknowledge the financial support provided for NETCARE through the Climate Change and Atmospheric Research Program at NSERC Canada. Thanks to Sangeeta Sharma, Desiree Toom, Andrew Platt, and the Alert operators for supporting the Alert observations. We are also grateful to Ilona Riipinen, Jan Julin, and Tinya Olenius for helpful discussions and for providing the Atmospheric Cluster Dynamics Code (ACDC), applied in our GEOS-Chem-TOMAS simulations. Edited by: H. Wang