We evaluate the impact of transport from midlatitudes on aerosol number concentrations in the accumulation mode (light-scattering particles (LSP) with diameters >180 nm) in the Arctic during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. We focus on transport from the Asian continent. We find marked contrasts in the number concentration (NLSP), transport efficiency (TEN_LSP, the fraction transported from sources to the Arctic), size distribution, and the chemical composition of aerosols between air parcels from anthropogenic sources in East Asia (Asian AN) and biomass burning sources in Russia and Kazakhstan (Russian BB). Asian AN air had lower NLSP and TEN_LSP (25 cm−3 and 18% in spring and 6.2 cm−3 and 3.0% in summer) than Russian BB air (280 cm−3 and 97% in spring and 36 cm−3 and 7.6% in summer) due to more efficient wet scavenging during transport from East Asia. Russian BB in this spring is the most important source of accumulation-mode aerosols over the Arctic, and BB emissions are found to be the primary source of aerosols within all the data in spring during ARCTAS. On the other hand, the contribution of Asian AN transport had a negligible effect on the accumulation-mode aerosol number concentration in the Arctic during ARCTAS. Compared with background air, NLSP was 2.3–4.7 times greater for Russian BB air but 2.4–2.6 times less for Asian AN air in both spring and summer. This result shows that the transport of Asian AN air decreases aerosol number concentrations in the Arctic, despite the large emissions of aerosols in East Asia. The very low aerosol number concentrations in Asian AN air were caused by wet removal during vertical transport in association with warm conveyor belts (WCBs). Therefore, this cleansing effect will be prominent for air transported via WCBs from other midlatitude regions and seasons. The inflow of clean midlatitude air can potentially have an important impact on accumulation-mode aerosol number concentrations in the Arctic.
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 Previous studies have suggested that Arctic pollution in the lower troposphere (LT) is mainly from northern Eurasia (Europe and Siberia) [e.g., Stohl, 2006; Law and Stohl, 2007; Klonecki et al., 2003; Huang et al., 2010]. However, the sources, transport pathways, removal processes, and distributions of aerosols in the Arctic are still uncertain, particularly in the middle and upper troposphere (MT and UT). Simulated aerosol concentrations in the Arctic are generally quite variable between models, primarily due to the different treatments of transport, transformation, and removal processes in different models [Shindell et al., 2008; Koch et al., 2009]. To reduce these uncertainties, it is essential to validate these model calculations with detailed measurements of aerosols (e.g., number and volume concentrations, chemical composition) and information on sources and transport processes.
 Aerosol number concentrations were measured extensively during the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) aircraft campaign conducted in and near the Arctic in April and June–July 2008 [Jacob et al., 2010]. Using these data, we evaluate the impacts of transport from the midlatitudes on aerosol number concentrations in the accumulation mode (measured diameters of 180–860 nm (section 2)) in the Arctic, especially from the Asian continent. We focus on air parcels from Asia because the ARCTAS measurements were made mainly over the Alaskan and Canadian Arctic region, which received air mostly originating from Asia [Fuelberg et al., 2010]. We characterize differences in accumulation-mode number concentration, size distribution, chemical composition, and transport efficiency of aerosols between air parcels influenced by anthropogenic emissions in East Asia (Asian AN) (e.g., China, Korea, and Japan) and emissions from biomass burning in Russia and Kazakhstan (Russian BB). Acronyms used in this study are summarized in Table 1.
Table 1. Acronyms Used in This Study
Mass concentration of BC
Number concentration of LSP and BC
Number concentration measured by CPC (>4 nm)
Volume concentration of LSP and BC
TEN_LSP, TEN_BC, TEV_LSP, TEM_BC
Transport efficiency of NLSP, NBC, VLSP, and MBC defined by equation (1)
FN_LSP, FN_BC, FV_LSP, FM_BC
Fractional source contribution to the total amount of NLSP, VLSP, NBC, and MBC defined by equation (2)
Average mass ratio of sulfate and organic aerosols to the total measured mass concentrations
Air parcel from anthropogenic sources in East Asia
Air parcel from biomass burning sources in Russia and Kazakhstan
Accumulated precipitation along individual trajectories
Warm conveyor belt
Cloud condensation nuclei
Aerosol indirect effect
2. Measurements and Methods
2.1. ARCTAS Observations
 Measurements of aerosols and other related species were made on board the NASA DC-8 aircraft during the ARCTAS aircraft campaign. Overviews of the ARCTAS campaign and meteorological conditions during the observation periods have been given by Jacob et al.  and Fuelberg et al. , respectively. In this study, we used North American Arctic data (one-minute average data), which was selected by Matsui et al.  (referred to as M2011, hereafter): 5 flights (Flights 06–10) over the Alaskan Arctic from 8 to 17 April (ARCTAS-A) and 2 flights (Flights 21–22) over the Canadian Arctic from 8 to 9 July (ARCTAS-B) (Figure 1). These data do not contain air parcels in the stratosphere (defined as ozone mixing ratio >120 ppbv) and in clouds (defined as liquid or ice water contents >0.01 g m−3) (M2011). M2011 suggested using satellite measurements that these flights during the ARCTAS-A and ARCTAS-B campaigns were representative of the North American Arctic in April and July 2008, respectively.
 The number and volume size distributions of light-scattering particles (LSP), which do not contain black carbon (BC) particles with volume-equivalent dry diameters larger than about 180 nm, were measured together with BC-containing particles by a Single Particle Soot Photometer (SP2) with high accuracy and temporal resolution [Moteki and Kondo, 2007]. We denote the measured number and volume concentrations of LSP at standard temperature and pressure (STP) as NLSP and VLSP, respectively, and number, mass, and volume concentrations of BC at STP as NBC, MBC, and VBC, respectively. Detailed descriptions of the SP2 used during the ARCTAS campaign are given elsewhere [Moteki and Kondo, 2010; Kondo et al., 2010, 2011]. During ARCTAS, the SP2 covered mass equivalent diameters of 80–860 nm for BC particles and 180–860 nm for LSP [Kondo et al., 2011]. LSP consisted of 89% and 97% of measured aerosol number and volume (LSP + BC), respectively, during the ARCTAS periods (average of 7 flights used in this study). Since the diameter of 180 nm corresponds approximately to the critical diameter of CCN at low supersaturations (supersaturation of about 0.1% and hygroscopicity of about 0.3 [Petters and Kreidenweis, 2007]), NLSP approximates the concentrations of particles that act as CCN at 0.1% supersaturation. We also used the measurements of carbon monoxide (CO) [Sachse et al., 1987], acetonitrile (CH3CN) [Wisthaler et al., 2002], dichloromethane (CH2Cl2) [Blake et al., 2003], the aerosol chemical composition of particulate matter smaller than 1 μm (PM1) [DeCarlo et al., 2006; Dunlea et al., 2009], the total aerosol number concentration (>4 nm) measured by condensation particle counters (NCPC) [Anderson et al., 1998], and aerosol volume concentrations in the coarse mode determined by a TSI Aerodynamic Particle Sizer (APS) Model 3321 (aerodynamic diameter of 0.7–5 μm). Since the lifetimes of CO, CH3CN, and CH2Cl2 are longer than one month in the atmosphere, we represent the short-term variability of these species by the differences between the measured and background concentrations of these species, denoted ΔCO, ΔCH3CN, and ΔCH2Cl2, respectively. The definitions of the background concentrations are given by M2011.
2.2. Methods of Data Analysis
 The methods of data analysis used in this study are similar to those of M2011. In brief, source regions of individual air parcels were estimated from 10-day backward trajectories released along the flight tracks [Fuelberg et al., 2010, and references therein]. The source regions were defined by M2011 as the boundary layer (BL) from the surface to 700 hPa over four regions: Europe, Russia (including Kazakhstan), Asia (including China, Korea, and Japan), and North America. We focus on source regions of Asia and Russia, shown in Figure 1. In this study, air parcels were classified as Russia, Asia, R+A (trajectories passing over source regions of both Russia and Asia), and other (from Europe or North America or source-unidentified data).
 It is a key issue to understand the relative contributions of AN and BB in the Arctic because recent studies suggested the importance of BB emissions to Arctic haze [e.g., Warneke et al., 2009, 2010]. In this study, source types (AN or BB) of individual air parcels were estimated from the concentrations of ΔCH2Cl2 and ΔCH3CN, which have been often used as tracers of AN and BB sources, respectively [e.g., Chen et al., 2007; Warneke et al., 2006]. AN air was defined as having high ΔCH2Cl2 (>5 pptv) and low ΔCH3CN (<100 pptv), while BB air was defined as having high ΔCH3CN (>50 pptv) and low ΔCH2Cl2 (<10 pptv) (Figure 3 of M2011). Air parcels with high ΔCH2Cl2 and ΔCH3CN were influenced by both AN and BB sources, and they are denoted as ANBB. The criteria of source regions and types was chosen so that we examine relatively fresh (within 10 days prior to measurement) air parcels clearly influenced by AN and BB emissions. As a result, the sources (both regions and types) were identified for about 25% of all the data (referred to as source-identified data) (M2011).
 We calculated accumulated precipitation along individual trajectories (APT) using Global Precipitation Climatology Project (GPCP) global precipitation data [Huffman et al., 2001; Adler et al., 2003] as in work by M2011. The amount of precipitation was summed (accumulated) along individual trajectories from where the air was sampled to when each trajectory reached one of the source regions (t hours before the measurements, dependent on trajectories) plus an additional 48 h within the sources, because air parcels may have already been influenced by precipitation within the source regions. Thus, the integration period for calculating the APT was t + 48 h (<10 days). The rationale for choosing the additional 48 h was discussed by M2011. Results did not change qualitatively when other integration periods (t + 24 h or t hours) were used for calculating APT values. We used the APT values as a measure of wet removal processes during transport. We note that APT is a broad measure because we use surface precipitation amounts. Precipitation may occur below air parcels, that does not affect aerosols in the air parcels.
 The ratios NLSP/ΔCO, VLSP/ΔCO, NBC/ΔCO, and MBC/ΔCO were used as indicators of the transport efficiency (TE) of NLSP (TEN_LSP), VLSP (TEV_LSP), NBC (TEN_BC), and MBC (TEM_BC), respectively, during transport from sources to the Arctic. TE values at time t were defined by the following equations.
In this equation, [NLSP/ΔCO]t, [VLSP/ΔCO]t, [NBC/ΔCO]t, and [MBC/ΔCO]t are the NLSP/ΔCO, VLSP/ΔCO, NBC/ΔCO, and MBC/ΔCO ratios at time t. The data with ΔCO > 20 ppbv were used for the statistical analysis. [NLSP/ΔCO]dry, [VLSP/ΔCO]dry, [NBC/ΔCO]dry, and [MBC/ΔCO]dry are the ratios for air with a minimum impact of wet removal processes. These dry ratios were estimated using AN and BB air data with APT < 5 mm in spring. We used these dry ratios obtained in spring also for summer, because of very limited data with APT < 5 mm for summer.
 Both numerators and denominators in equation (1) include the increase in VLSP and NLSP by condensation and nucleation processes and the decrease in NLSP and NBC by coagulation processes during transport from sources to the Arctic. Therefore, these processes will partly compensate each other in the TE calculations using equation (1). As a result, we can regard the TE values as a measure of transport efficiency mostly due to removal processes during transport.
 We note that the dry ratios for AN air were derived mainly from North American air, because there are few Asian air data with APT < 5 mm. The TE values in Asian AN air are likely overestimates, because the dry ratios of NLSP/ΔCO, VLSP/ΔCO, NBC/ΔCO, and MBC/ΔCO observed in East Asia (A-FORCE aircraft campaign (N. Oshima et al., Wet removal of black carbon in Asian outflow: Aerosol Radiative Forcing in East Asia (A-FORCE) aircraft campaign, submitted to Journal of Geophysical Research, 2011)) were measured to be about 1.4 times higher than those of AN air estimated in this study.
3. Transport Pathways and Processes of Air Parcels
 The transport pathways and processes of measured air parcels have been already analyzed in detail by M2011. Here we briefly summarize their main findings and provide additional results from the viewpoint of the contrast between Asian AN and Russian BB air. During the springtime, most Asian AN air parcels originated from lower latitudes (30°–40°N) with high relative humidity. They then underwent rapid ascent on the warmer side of cold fronts associated with low-pressure systems and were transported northward and reached the Arctic within a few days after experiencing heavy precipitation and large amounts of latent heating (Figure 2a). These transport pathways are frequently seen in this region and season and are generally due to warm conveyor belts (WCBs) [e.g., Stohl, 2001; Eckhardt et al., 2003; Oshima et al., 2004; Harrigan et al., 2011; Sessions et al., 2010]. The median APT value was 24 mm for Asian AN air (Table 2). The median transport time from their source (from WCB lifting) to the measurement sites was 7.8 (2.4) days. Since the Asian AN air had relatively high potential temperature at its source and experienced further diabatic heating (due to latent heat release during the WCB ascent), they were generally observed in the UT (300–500 hPa), as shown in Figure 3.
Table 2. Statistics of Individual Air Parcels During the ARCTAS Campaign
RA denotes the average mass ratio of species A to the total measured submicron mass concentration (non-refractory PM1 from the AMS plus BC from the SP2).
APT denotes accumulated precipitation along trajectories.
Russia + Asia
Russia + Asia
 On the other hand, Russian BB air parcels were transported almost isentropically from higher latitudes (50°–70°N), hence they encountered less precipitation and latent heating (Figure 2b). The median APT value was 8.5 mm for Russian BB air (Table 2). The median transport time from their source to the Arctic was 3.5 days. Since Russian BB air had lower potential temperature in the source regions and experienced quasi-adiabatic transport, it was mostly observed in the MT (500–700 hPa) (Figure 3). As a result, the median MBC and TEM_BC values were much less for Asian AN air (18 ng m−3 and 13%, respectively) than for Russian BB air (266 ng m−3 and 83%, respectively).
 The median APT during summer was much greater (17 mm) than during spring (3.2 mm) for all flight data used in this study. This was mainly due to the greater precipitation and accompanying wet scavenging over the latitudes 45°–70°N during summer. Correspondingly, the TEM_BC values for both Russian BB and Asian AN air were much lower during summer (4.0 and 0.76%, respectively) than during spring (83 and 13%, respectively). The median MBC for all measured air parcels in the Arctic was 5.7 ng m−3, which is 10 times less than during spring (55 ng m−3), while the median ΔCO mixing ratio was somewhat higher than during spring (23 ppbv versus 14 ppbv).
 The high TEM_BC − APT correlation (R2 = 0.80 between median values of log (TEM_BC) and APT for individual sources and seasons, Figure 13b of M2011), together with the seasonal variations in APT, suggest that the large seasonal variations in MBC were caused mainly by those in the wet removal rates. The contribution of Russian BB in spring to the MBC in the North American Arctic was largest, because of the spring maximum in TEM_BC with low precipitation at higher latitudes.
4. Variation of Accumulation-Mode Aerosol Number Concentration
4.1. Transport Efficiency of NLSP and NBC From Asia to the Arctic
 Because the transport and removal processes differed greatly between Asian AN and Russian BB air parcels, as shown in section 3, these processes should also affect the NLSP of individual air parcels. Figure 4 shows the scatterplot between the NLSP/ΔCO ratio and APT for all data (including both source-identified and source-unidentified data) used in this study and that for individual source regions and types (AN and BB). On average, the NLSP/ΔCO ratio decreased with increasing APT in both spring and summer, indicating that removal by precipitation is one of the most important processes in controlling NLSP in the Arctic. This tendency does not change even if Russian BB and Asian AN data are excluded. The NLSP/ΔCO ratio was low at high APT values for Asian AN air, which was mostly measured in the UT. In contrast, the NLSP/ΔCO ratio was much higher for Russian BB air parcels, which were mainly transported to the Arctic MT with low APT (sections 3 and 4.2). These results are similar to those for MBC discussed in M2011.
Figures 5a and 5b show that NLSP and NBC had high correlations for all the data used in this study (gray dots in Figures 5a and 5b) during both spring (R2 = 0.87) and summer (R2 = 0.57). The median NLSP and NBC in spring were 25.4 and 2.8 cm−3 for Asian AN air, 280 and 40.5 cm−3 for Russian BB air, and 79.6 and 7.5 cm−3 for all the data for spring used in this study, respectively (Table 2). The lower number concentrations (both LSP and BC) in Asian AN air were due to the effective wet scavenging of aerosols during WCB transport, and the higher concentrations in Russian BB air were due to the efficient transport of aerosols. The number concentrations (both LSP and BC) during summer were systematically less than those during spring. This was mainly due to the greater precipitation over the latitudes 45°–70°N in summer (section 3 and M2011). The median values of NLSP and NBC in summer were 6.2 and 0.33 cm−3 for Asian AN air, 36.4 and 2.1 cm−3 for Russian BB and ANBB air, and 18.6 and 1.2 cm−3 for all the data for summer, respectively (Table 2). Similar good correlation and seasonal variation was found between VLSP and MBC (R2 = 0.87 for spring and R2 = 0.73 for summer). The NLSP/NBC ratio was a factor of 2–4 higher during summer than spring for individual sources (Table 2). This seasonal variation is qualitatively consistent with surface measurements of aerosol optical properties at Barrow [Quinn et al., 2002]. Since the number of data used in this study is very limited especially during summer (two flights), further studies are needed to understand whether this seasonality is general in the Arctic, including MT and UT.
Figure 5c shows the correlation between median values of TEN_LSP and TEN_BC for individual source regions and types in both spring (closed circles) and summer (open squares). The median TE values were highly correlated with R2 = 0.88 (Figure 5c). Due to the differences in transport and removal processes, the median TEN_LSP and TEN_BC values were much greater for Russian BB air (97 and 85%, respectively) than for Asian AN air (18 and 18%, respectively) in spring. In addition, TE values during spring were systematically higher than those in summer (Figure 5c and Table 3). These variations in TE are similar to those in TEM_BC (M2011). The median TEV_LSP and TEM_BC were also highly correlated (R2 = 0.90) (Figure 5d). The TEV_LSP/TEM_BC ratio for summer was higher than during spring (Figures 5c and 5d and Table 3). This is consistent with the NLSP/NBC ratio because we used the same dry ratio (the NLSP/ΔCO, VLSP/ΔCO, NBC/ΔCO, and MBC/ΔCO ratios with APT < 5 mm) for summer and spring to derive the TE values for summer (section 2.2 and M2011). The dry ratios in summer might be higher than during spring in the real atmosphere due to faster growth and formation rates of LSP by a higher oxidation rate during transport.
Table 3. Transport Efficiency (TE) and Fractional Contribution (F) of Individual Air Parcels During the ARCTAS Campaign
 NLSP, VLSP, NBC, and MBC and their TE values were tightly correlated (Figure 5), indicating that LSP and BC had similar or collocated (at the horizontal scale of this study) emission sources and experienced similar levels of removal processes for both number and volume concentrations (>180 nm) during transport from their sources to the Arctic. We interpret similar TE values between LSP and BC as due to sufficient processing of BC during transport, resulting in hygroscopicity as high as that of LSP particles. This interpretation is supported by the long transport time from sources to the Arctic (section 3) and observed thick coatings of BC particles. Specifically, the median value of the shell (LSP + BC) to core (BC) diameter ratio in spring was 1.51 and 1.35 for Russian BB and Asian AN air, respectively, for a core diameter of 200 nm, although it should be noted that measured particles were not scavenged during transport but survived wet removal processes.
 We calculated the contributions of individual sources to the total NLSP, VLSP, NBC, and MBC in the North American Arctic (sum of the measured concentration for all source-identified data) using the following equations (2).
FN_LSP,i, FV_LSP,i, FN_BC,i, and FM_BC,i are the fractional contribution of source i to the total amount of NLSP, VLSP, NBC, and MBC, respectively. NLSP,i,t, VLSP,i,t, NBC,i,t, and MBC,i,t are NLSP, VLSP, NBC, and MBC at time t from source i, respectively, while j means summation of the values for all sources. The fractional contribution of NLSP, VLSP, NBC, and MBC for BB air that passed over Russia (sum of BB and ANBB sources from Russian, Russia + Asia, and Russia + Europe) was as high as 60% in spring and 66% in summer (Table 3), indicating that Russian BB was the dominant source of aerosol (for both LSP and BC and for both number and volume concentrations) within the source-identified data. In contrast, the fractional contribution from Asian AN air was as low as 2–3% in spring and 7–9% in summer within the source-identified data (Table 3), indicating the very limited impact from Asian AN sources on Arctic aerosol.
 The contribution from BB and AN sources (including data of unidentified source regions) to all the data (both source-identified and source-unidentified data) in spring was estimated to be 42–48% and 25–27%, respectively, for NLSP, VLSP, NBC, and MBC (the remainder is data of unidentified source types) (Figure 6). This result suggests that BB emissions were the primary source of aerosol (for both LSP and BC and for both number and volume concentrations) in the North American Arctic in spring 2008. Although the source regions were not identified for more than 50% of the data in BB by trajectory calculations, most BB-influenced air probably originated from Russia and Kazakhstan considering that few data were from other BB sources within the source-identified data during spring (Table 2 of M2011).
 In summary, Russian BB in spring was the most important source of accumulation-mode aerosols over the Arctic for both LSP and BC and for both number and volume concentrations during the ARCTAS campaign within the source-identified data. BB emissions were found to be the primary source of aerosol within all the data in spring during ARCTAS. In contrast, Asian AN air provided a negligible contribution to the accumulation-mode aerosols (both LSP and BC) over the North American Arctic in both spring and summer 2008.
4.2. Vertical Profile of NLSP
Figure 7 shows the vertical profiles of NLSP measured during spring and summer. NLSP had a broad maximum in the MT in spring. This profile is similar to that of MBC shown in M2011. We can interpret this vertical profile by the differences in TEN_LSP (Figure 5c and Table 3) and the differences in altitude profiles (Figure 3) between the Asian AN and Russian BB air parcels. The broad peak in the MT was due to the dominant contribution of Russian BB. The decrease in the UT was due to efficient wet removal of LSP in Asian AN air. The shapes of the vertical profiles of VLSP and NBC were similar to that of NLSP (not shown).
4.3. Comparison of NLSP With Background Aerosol Concentrations
 The values of NLSP in Asian AN and Russian BB air were compared with those of background air. We defined background air as source regions that were not identified (not from Europe, Russia, Asia, or North America) based on trajectory calculations and had concentrations of ΔCO, ΔCH3CN, and ΔCH2Cl2 that were less than 5 ppbv, 50 pptv, and 5 pptv, respectively. Compared with background air, the median NLSP for Russian BB air were factors of 4.7 and 2.3 greater during spring and summer, respectively, while those of Asian AN air were factors of 2.4 and 2.6 smaller in spring and summer, respectively (Figure 8 and Table 2). These features were also seen for VLSP, NBC, and MBC (Table 2). This result indicates that inflow of midlatitude Asian AN air decreased aerosol concentrations in the Arctic (cleansing effect). The high concentrations of ΔCO (levels similar to Russian BB air) for AN air suggest high concentrations of aerosols and their precursors in the source region.
 WCBs are a common synoptic-scale transport mechanism over various regions at midlatitudes and seasons [Stohl, 2001; Eckhardt et al., 2003]. Aerosol concentrations in air transported via this mechanism from midlatitudes will generally be lower than that in background Arctic air. This process can be one of the most important processes in controlling aerosol concentrations in the MT and UT in the Arctic in spring and summer. Further studies, especially using chemical transport models, are needed to assess the effect more quantitatively, including the frequency of inflow of clean midlatitude air to the Arctic.
4.4. Chemical Composition of LSP
 Asian AN and Russian BB air also had marked differences in aerosol chemical composition. The average mass ratio of sulfate aerosol to the total PM1 mass concentrations (RSO4) was largest (67% in spring and 59% in summer) in Asian AN air, while that of organic aerosol (RORG) was largest (61% in spring and 68% in summer) in Russian BB air during both spring and summer (Table 2 and Figure 9). This reflects characteristics of the emissions of trace gases and aerosols in the Asian continent. In fact, based on emission inventories for the Asian continent, the mass emission ratio between SO2 and primary organic carbon is about 1–2 orders of magnitude greater for anthropogenic sources in Asia (7.2, SO2 dominant) [Zhang et al., 2009] than for biomass burning sources in East Asia (0.11, organic carbon dominant) [Streets et al., 2003], although the relative contribution of secondary organic aerosol formation during transport might be larger for AN air than BB air [Cubison et al., 2011]. The sulfate mass fraction was as large as about 30% in Russian BB air (Table 2 and Figure 9). Sulfate in Russian BB air could be from SO2 emission from fires in the flaming phase and their oxidation to sulfate [Kondo et al., 2011] and mixing with background air, which includes high fractions of sulfate (Table 2 and Figure 9c).
 The background air parcels in spring had chemical compositions similar to Asian AN air (high sulfate/organics ratio), suggesting that they could have been influenced mainly by AN sources (Figure 9c). On the other hand, the background air in summer had a greater fraction of organics (Figure 9f), suggesting that they had been influenced by both AN and BB sources. This result implies that Arctic background aerosols during winter and early spring are mainly from AN sources, while BB emissions taking place from spring to summer may alter aerosol concentrations and chemical compositions in the Arctic by summer.
 Chemical compositions (average mass ratio) in spring shown in Figure 9 are generally consistent with the measurements during the Aerosol, Radiation, and Cloud Processes affecting Arctic Climate (ARCPAC) aircraft campaign in spring 2008 [Brock et al., 2011]. Both studies showed that organics were dominant (about 60% of fine particles) for BB air parcels and comprised 20–30% of fine particles for AN air parcels. The contribution of sulfate in background air was slightly higher during ARCTAS (about 60%) than ARCPAC (about 50%). The contribution of BC was about 3–5% of fine particles for all air parcels.
4.5. Size Distribution of LSP
 Asian AN and Russian BB also exhibit marked differences in the normalized size distribution of VLSP (Figure 10), which is defined for all one-minute data as the size distribution of VLSP normalized by the total VLSP: Russian BB air had nearly a single lognormal distribution with a peak diameter of 250 nm, while Asian AN air had a two-mode lognormal distribution with peak diameters of 250 and 530 nm (although the absolute concentrations were an order of magnitude less than Russian BB air, as shown in Table 2). The widths of size distributions were narrow for both NLSP (1.20–1.23) and VLSP (1.24–1.30) for both Russian BB and Asian AN air. These standard deviations are generally consistent with those calculated from the peak diameters of number and volume size distributions when lognormal distributions are assumed. Compared with Brock et al. , our measurements during spring had greater peak diameters of number size distributions and smaller peak diameters of volume size distributions and standard deviations for all air parcels.
 The larger mode of Asian AN air is possibly due to aqueous-phase aerosol growth within cloud droplets during transport. The dispersions of the size distribution (vertical bars in Figure 10a) for Asian AN air were larger than for Russian BB air (Figure 10b) for LSP. These results are consistent with a stronger impact of wet removal processes for Asian AN air. In addition to the aqueous-phase growth, mixing with background air, which contained moderate concentrations of larger particles (Figure 10c), could be a source of the larger mode of Asian AN air. Dust particles might be another potential source of larger particles [Leaitch et al., 2009; McKendry et al., 2011], but the median volume concentrations of coarse particles derived by APS (0.12 μm3 cm−3) were considerably smaller compared with those of the accumulation mode derived by SP2 (0.49 μm3 cm−3) for Asian AN air parcels during spring. The contribution from mixing of BB air to Asian AN air should be limited for both smaller and larger modes because of the strict criteria for choosing Asian AN air (low concentrations of ΔCH3Cl).
 Finally, we note that total aerosol number concentrations (NCPC) and NLSP exhibited very different variations during ARCTAS. The median NLSP/NCPC ratio for Asian AN (Russian BB) air was 0.08 (0.53) in spring and 0.05 (0.09) in summer during ARCTAS. The Aitken and nucleation-mode particles were dominant when the accumulation-mode particles were low, suggesting that new particle formation might have occurred in these air parcels during transport after the wet scavenging of accumulation-mode particles. This tendency is consistent with previous measurements of air transport from Asian sources [Brock et al., 2004; Dunlea et al., 2009; Weber et al., 2003].
5. Potential of Aerosol-Cloud Interaction
 We briefly discuss the potential impacts of the transport of polluted (Russian BB) and clean (Asian AN) air on aerosol-cloud interactions in the Arctic, based on the findings of recent studies. The median NLSP of Russian BB air was 280 cm−3 in spring. Lubin and Vogelmann  estimated a longwave aerosol indirect effect (AIE) of 3.4 W m−2 for Arctic stratus clouds, which contain aerosol number concentrations greater than 175 cm−3. Assuming a case in which Russian BB air forms stratus clouds in the Arctic, they could have an equivalent or greater potential of cloud-radiation feedback (longwave indirect warming effect) than that presented by Lubin and Vogelmann .
 On the other hand, when shortwave AIE is included, the total (longwave + shortwave) first AIE can be positive during early spring (March–April) but negative in late spring and summer (April–July) [Lubin and Vogelmann, 2010; Alterskjær et al., 2010] because shortwave solar radiation increases with the progression of the seasons. Longwave and shortwave AIEs will generally compensate for each other in spring. The onset of BB in Russia in 2008 corresponds to the transition period from positive to negative total first AIE. An earlier onset of Russian BB in the future [Stocks et al., 1998] may contribute to an additional Arctic warming by the total first AIE.
 Some studies suggest that the entrainment of CCN and ice nuclei into Arctic stratus clouds in the LT can contribute to increases in cloud droplet number, liquid water path, and cloud optical depth [Jiang et al., 2001], and possibly affect the acceleration of snow-ice melting [Carrió et al., 2005a, 2005b]. Russian BB aerosols in the MT have the potential to be entrained into the BL and could contribute to Arctic warming by this effect and resulting dynamical changes. Since Russian BB air may have both warming (longwave AIE and entrainment of ML air to the BL) and cooling (shortwave AIE) effects, as shown above, more detailed studies are needed to understand the relative importance of the individual effects quantitatively.
 Since Asian AN air had lower NLSP than background air, these air parcels may cause opposite aerosol indirect effects through the reduction of cloud emissivity and lifetime (compared with background air). In addition, since the median NLSP of Asian AN air was only 6.2 cm−3 in summer, cloud formation and precipitation processes (if we assume a case with supersaturated conditions) could be limited by the available CCN concentration, as proposed by Mauritsen et al. . This cloud regime may cause higher supersaturation, increase precipitation efficiency, cause a positive feedback on the aerosol by increased wet deposition, and produce lower aerosol concentrations in the Arctic [Mauritsen et al., 2011]. Therefore, Asian AN may have additional cleansing effects by this aerosol-cloud-precipitation interaction in the Arctic if this effect could be applied to the UT.
 We have evaluated the impacts of transport of midlatitude air on aerosol number concentrations in the accumulation mode (light scattering particles (LSP) with diameters >180 nm, NLSP) in the Arctic during the ARCTAS aircraft campaign conducted in April and June–July 2008. We focused on air parcels transported from anthropogenic sources in East Asia (Asian AN) and biomass burning sources in Russia and Kazakhstan (Russian BB). Most Asian AN air parcels were transported from lower latitudes (30°–40°N) and had fairly high relative humidity. They experienced rapid ascent by warm conveyor belts (WCBs) with heavy precipitation, while Russian BB air parcels were transported almost isentropically from higher latitudes (50°–70°N) and encountered less precipitation.
 Due to these differences in transport processes, we found marked differences in the number concentration (NLSP), transport efficiency (TEN_LSP), size distribution, and chemical composition of aerosols between Asian AN and Russian BB air. Asian AN air had lower NLSP and TEN_LSP (25 cm−3 and 18% in spring and 6.2 cm−3 and 3.0% in summer) than Russian BB air (280 cm−3 and 97% in spring and 36 cm−3 and 7.6% in summer) due to more intense wet scavenging during transport from Asia. NLSP and TEN_LSP in summer were much lower than those in spring for both sources. Russian BB air had nearly a single lognormal distribution of aerosol volume concentrations (VLSP) with a peak diameter of 250 nm, while Asian AN air had a two-mode lognormal distribution with peak diameters of 250 and 530 nm. The size distribution was narrow (standard deviation of 1.2–1.3) for both Russian BB and Asian AN air. The second peak of VLSP in Asian AN air is likely droplet-mode aerosols, which are consistent with WCB transport with efficient cloud and precipitation processes. Sulfate and organic aerosols were dominant in Asian AN and Russian BB air, respectively, reflecting emission sources. The chemical compositions of background air parcels suggest that they were mainly influenced by AN sources in spring and both AN and BB sources in summer. This result implies that BB emissions from spring to summer alter aerosol concentrations and chemical compositions in the Arctic.
 NLSP, VLSP, and number and mass concentrations of BC and their TE values were tightly correlated, indicating that LSP and BC were sufficiently processed and had experienced similar levels of removal processes during transport from their sources to the Arctic. Within the source-identified data, Russian BB in spring was the largest and most important source of accumulation-mode aerosols for both LSP and BC and for both number and volume concentrations during the ARCTAS campaign (60–70% of total accumulation-mode aerosols). On the other hand, the transport of Asian AN air contributed little to both LSP and BC in the Arctic in spring and summer (less than 10% of total accumulation-mode aerosols). The contribution from BB and AN sources to all the data (both source-identified and source-unidentified data) in spring was estimated to be 42–48% and 25–27%, respectively, for NLSP, VLSP, NBC, and MBC, suggesting that BB emissions were the primary source of aerosol (for both LSP and BC and for both number and volume concentrations) in the North American Arctic in spring 2008.
 The median NLSP of Russian BB air were factors of 4.7 and 2.3 higher than those of background air in spring and summer, respectively, while those of Asian AN air were factors of 2.4 and 2.6 lower than those of background air in spring and summer, respectively. The latter was due to wet removal during WCB transport and indicates that Asian AN air can reduce aerosol concentrations in the Arctic (cleansing effect). Since WCBs are a common synoptic-scale transport mechanism over the midlatitudes, it is expected that the transport of midlatitude air can be a source of clean air (in terms of aerosols) in the Arctic in spring and summer. Further studies are needed to quantify this effect on the climate of the Arctic.
 The ARCTAS campaign was supported by NASA. We are indebted to all the ARCTAS participants for their cooperation and support. Special thanks are due to the flight and ground crews of the NASA DC-8 aircraft. We thank M. Osuka for his assistance with the field measurements. This work was supported in part by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), the strategic international cooperative program of the Japan Science and Technology Agency (JST), and the global environment research fund of the Japanese Ministry of the Environment (A1101). Y.Z. was supported in part by NASA's Tropospheric Chemistry Program (USP-SMD-08-009). CH3CN measurements were supported by the Austrian Research Promotion Agency (FFG-ALR) and the Tiroler Zukunftstiftung and were carried out with the help/support of T. Mikoviny, M. Graus, A. Hansel, and T. D. Maerk. M.J.C. and J.L.J. were supported by NASA NNX08AD39G.