Deposition velocity of ultrafine particles measured - Wiley Online Library

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, D16202, doi:10.1029/2009JD013600, 2010

Deposition velocity of ultrafine particles measured with the Eddy‐Correlation Method over the Nansen Ice Sheet (Antarctica) D. Contini,1 A. Donateo,1 F. Belosi,2 F. M. Grasso,1 G. Santachiara,2 and F. Prodi2 Received 23 November 2009; revised 26 March 2010; accepted 6 April 2010; published 18 August 2010.

[1] This work reports an analysis of the concentration, size distribution, and deposition velocity of atmospheric particles over snow and iced surfaces on the Nansen Ice Sheet (Antarctica). Measurements were performed using the eddy‐correlation method at a remote site during the XXII Italian expedition of the National Research Program in Antarctica (PNRA) in 2006. The measurement system was based on a condensation particle counter (CPC) able to measure particles down to 9 nm in diameter with a 50% efficiency and a Differential Mobility Particle Sizer for evaluating particle size distributions from 11 to 521 nm diameter in 39 channels. A method based on postprocessing with digital filters was developed to take into account the effect of the slow time response of the CPC. The average number concentration was 1338 cm−3 (median, 978 cm−3; interquartile range, 435–1854 cm−3). Higher concentrations were observed at low wind velocities. Results gave an average deposition velocity of 0.47 mm/s (median, 0.19 mm/s; interquartile range, −0.21 −0.88 mm/s). Deposition increased with the friction velocity and was on average 0.86 mm/s during katabatic wind characterized by velocities higher than 4 m/s. Observed size distributions generally presented two distinct modes, the first at approximately 15–20 nm and the second (representing on average 70% of the total particles) at 60–70 nm. Under strong‐wind conditions, the second mode dominated the average size distribution. Citation: Contini, D., A. Donateo, F. Belosi, F. M. Grasso, G. Santachiara, and F. Prodi (2010), Deposition velocity of ultrafine particles measured with the Eddy‐Correlation Method over the Nansen Ice Sheet (Antarctica), J. Geophys. Res., 115, D16202, doi:10.1029/2009JD013600.

1. Introduction [2] Concentrations of anthropogenic aerosols have increased markedly since preindustrial times, while the concentrations of natural aerosols have remained roughly at the same level. The Antarctic atmosphere, although not meteorologically isolated from the rest of the planet, may be considered one of the regions least perturbed by pollutants, playing a fundamental role in determining the global climate. Suspended particles constitute an important component of the atmosphere, and their dynamics in the surface layer determines deposition on snow or ice surfaces and trapping of aerosol in the ice. Over the years aerosols in remote regions such as the Arctic and Antarctic have been investigated with regard to chemical composition [Harvey et al., 1991; Savoie et al., 1992; Minikin et al., 1998; Fattori et al., 2005; Virkkula et al., 2006], total number and mass concentrations [Jaenicke et al., 1992; Mazzera et al., 2001], optical properties [Tomasi et al., 2007], ability to act as cloud condensation nuclei [Harder et al., 1996; De Felice et al., 1997], and number and chemical mass size distribution [Harvey 1 Istituto di Scienze dell’Atmosfera e del Clima, ISAC‐CNR, Lecce, Italy. 2 Istituto di Scienze dell’Atmosfera e del Clima, ISAC‐CNR, Bologna, Italy.

Copyright 2010 by the American Geophysical Union. 0148‐0227/10/2009JD013600

et al., 1991; Jaenicke et al., 1992; Ito, 1993; Brechtel et al., 1998; Teinila et al., 2000; Nilsson and Rannik, 2001; Koponen et al., 2003; Park et al., 2004]. A complete review of aerosol deposition measurements on different surfaces is reported by Pryor et al. [2008]. Gallagher et al. [2002] provides a review of available data on deposition velocity over surfaces of different roughness height, including snow. Relatively few cases exist of aerosol deposition measurements on snow or iced surfaces, especially using the eddy‐correlation (EC) method. The first example was reported by Duann et al. [1988], who analyzed deposition of particles in two size ranges (0.15–0.30 and 0.5–1.0 mm) using the EC in a snow‐ covered field in central Pennsylvania. Successively, Nilsson and Rannik [2001] used the EC method to measure the deposition velocity of particles larger than 10 nm in diameter over smooth ice and rough ice in the Arctic ice pack. The only measurements carried out in Antarctica were reported by Gronlund et al. [2002], who analyzed the deposition velocity of particles larger than 10 nm over ice surface at Wasa and Aboa (Dronning Maud Land). Available results show some significant differences in the results in terms of average deposition velocity and of correlation between deposition velocity and friction velocity. Some analyses of aerosol deposition over snow and ice surfaces have also been performed on mass fluxes of different species [Ibrahim et al., 1983; Cadle et al., 1985; Davidson et al., 1985; Hillamo et al., 1993].

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CONTINI ET AL.: DEPOSITION VELOCITY IN ANTARCTICA

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Figure 1. (a) Satellite image showing the position of the measurement system over the Nansen Ice Sheet and the Italian Base “Mario Zucchelli.” (b) Schematic of the position of the measurement site with respect to the Italian base activity and to the electric power supply (not in scale). [3] The aim of the present work is to analyze the deposition velocity of atmospheric particles on snow surfaces in a remote glacier of Antarctica and their size distributions in relation to local micrometeorological conditions. Vertical turbulent fluxes of particles were measured using the EC method. Results are discussed in terms of average concentration, deposition velocity, and the relationship between deposition, friction velocity, and stability.

with a simple two‐channel interface. The first channel was used to measure concentrations lower than 1000 cm−3, and the second was used for concentrations between 1000 and 10,000 cm−3. Aerosol was sampled roughly at the same

2. Instruments and Methods [4] Aerosol particle number concentration, number size distribution, and vertical turbulent flux measurements were performed during austral summer 2006, between 8 and 31 December, in the framework of the XXII Italian Antarctic expedition (2006–2007) of the Italian National Program for Research in Antarctica (PNRA). (The sampling site is located over the Nansen Ice Sheet (74°30′02″S, 163°27′30″W; 84.7 m above level sea), as shown in Figure 1. This is a permanently iced branch of the Ross Sea of about 35 × 70 km extent, encroaching inland. Because of its remote inland location the site is ideal for sampling unperturbed atmospheric aerosol characteristics. The distance to the open sea (Ross Sea) is about 50 km and it is about 30 km NW of the Italian Station “Mario Zucchelli” as shown in Figure 1. 2.1. Sampling Instrumentation [5] Measurements were carried out using a micrometeorological flux system based on the EC method. The system was placed on a tower at 12 m height (Figure 2). The system included a condensation particle counter (CPC; Grimm Aerosol Model 5.403) that measured the total particle number concentrations at 1 Hz. The performances of this CPC are analyzed by Heim et al. [2004]. Wind components (u, v, w) were measured at 100 Hz with an ultrasonic anemometer (Gill Instruments R3), which also measured sonic temperature. The CPC output was connected to the analog inputs of the anemometer by means of a digital‐to‐analog conversion

Figure 2. Experimental setup over the Nansen Ice Sheet: (a) instrumented tower and glass‐fiber igloo. (b) Unleaded gasoline electricity generator located about 500 m from the tower. (c) Upper part of the tower, with the sonic anemometer, aerosol inlet, fast hygrometer KH20, and net radiometer. (d) Interior of the igloo, with a notebook for data processing and storage, pumps, condensation particle counter (CPC), and Differential Mobility Particle Sizer (DMPS).

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Figure 3. Inlet penetration factor and total counting efficiency of the system used to measure particle number concentrations. height as the sensing head of the anemometer (about 35 cm from its sensing volume) through a 10.5 m long sampling inlet (anodized aluminium) of 26 mm internal diameter. A pump (Tecora Bravo H‐plus) was used to maintain a flow‐ rate of 45 L/min in the inlet tube, giving a turbulent flow with a Reynolds number of about 2550 and minimizing the temporal distortion of concentration fluctuations. A portion of 1.5 L/min was taken from the main flow at the end of the inlet tube using a 0.8 m long conductive plastic tube (6 mm internal diameter) and injected into the CPC. The particle losses for the inlet system were calculated according to the formulation of Baron and Willeke [2001] for the laminar flow inside the last part of the inlet and according to Hinds [1999] for turbulent flow in the large section tube. The particle penetration curve through the inlet is reported in Figure 3, together with the total counting efficiency, calculated as the product between the penetration factor and the counting efficiency of the CPC obtained from Heim et al. [2004]. The results show that the cutoff diameter (at 50% efficiency), D50, is about 9 nm. According to Heim et al. [2004], the D50 of the Grimm 5.403 CPC is 7.5 nm under normal laboratory conditions. Therefore, the effect on D50 of additional losses included in the measurement system is probably negligible for the purposes of the flux measurements presented here. Therefore, the system used was able to detect particles of between 9 and 1000 nm (i.e., the upper limit of the CPC). The analysis reported by Heim et al. [2004], using laboratory‐generated NaCl aerosol (with a size distribution centred at 52 nm in diameter), shows that the performances in concentration measurement of this CPC are perfectly comparable with those of others, like TSI 3010 and TSI3022, in the concentration range lower than 20,000 cm−3. Heim et al. [2004] also analyzed the time response to a concentration step, showing a dependency of the time response on the concentration step, being lower at a low concentration. The time response could be described by a combination of a laminar flow reactor in series with a plug flow reactor with associated time constants, respectively, of 3.37 and 0.63 s. A laboratory analysis was performed on the time response of the CPC to a step in number concentration, obtaining, as the average of several repeated trials, a first‐ order time response t C of about 1.3 s, in good agreement

with the results reported by Heim et al. [2004]. A fast (100 Hz) open‐path hygrometer (KH20; Campbell Scientific) was included in the micrometeorological system to measure water vapor concentration fluctuations and, thus, latent/ sublimation heat flux. The system also included a net radiometer and a slow‐response thermohygrometer (Rotronic MP100A). According to the user’s manual, the MP100A has an operational range of between −40° and 60°C, with an uncertainty (at 23°C) in temperature of ±0.3°C and an uncertainty in measurement of relative humidity of ±2%. The Differential Mobility Particle Sizer (DMPS), CPC, two pumps, and data acquisition computer were placed in a small igloo made of glass fiber located at the base of the tower (Figure 2). [6] The particle size distributions were measured by a DMPS (Model 5.500, Grimm aerosol) every 6 min. The DMPS sampled air at a height of 2.5 m and was operated using a second inlet tube 130 cm long (internal diameter, 30 mm) with a flow rate of 10 L/min, maintained by a second vacuum pump. A fraction of 0.3 L/min was channeled to the DMPS through a conductive plastic tube 37 cm long and 6 mm in internal diameter. The DMPS was configured to evaluate size distributions for particles between 11 and 521 nm in diameter using 39 channels. The measured size distributions were corrected taking into account particle losses inside this inlet, as evaluated according to Baron and Willeke [2001]. [7] The electric power for all the instruments was supplied by an unleaded gasoline generator through a UPS system (3 kW). The generator was installed at a distance of approximately 500 m from the tower in the SE direction (at about 145°), as shown in Figure 2. Therefore, contamination due to the presence of the generator was possible under specific meteorological conditions, necessitating the development of a procedure to eliminate contaminated cases from the measured concentrations, as described here. 2.2. Data Processing [8] The EC method was based on the separation of aerosol number concentration and vertical wind component into mean values (N , w) and turbulent fluctuations (N′, w′) [Businger, 1986; Moncrieff et al., 1997]. The measured time

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series were first despiked and subsequently treated with a three‐dimensional rotation to use the local streamline reference system [McMillen, 1988]. Then the mean and fluctuating parts were extracted by performing a linear detrending [Buzorius et al., 1998; Rannik and Vesala, 1999]. The chosen reference averaging time was 30 min. Vertical turbulent aerosol fluxes w0 N 0 were then calculated, along with those for momentum and energy. To account for the lag time introduced by the sampling inlet to the CPC, a fixed delay time of 12 s was adopted and the time series was shifted accordingly prior to calculating the aerosol fluxes. The lag time was based on laboratory tests of the complete system and confirmed the choice of a cross‐correlation analysis of the time series of vertical wind and aerosol number concentration as a function of lag time. Particle number fluxes are generally reported normalized in terms of deposition velocity [Vong et al., 2004; Pryor, 2006]: Vd ¼

w0 N 0 FN ¼ : N N

ð1Þ

A stationarity test was performed for particle concentration data series, after the detrending process, as described by Mahrt [1998], choosing a threshold for the nonstationarity index of 2, which gave good results in the analysis reported in the work by Cava et al. [2008]. The percentage nonstationary data was 15% of the whole measurement period, and such cases were removed from subsequent analyses. [9] The sensible heat flux H and the sublimation heat flux E were calculated using H = cp rw0 T 0 and E = rlSw0 0v , where r is the air density, rv is the water vapor concentration, cp = 1005 J/K/kg is the specific heat at constant pressure, lS = 2.83 × 106 J/kg is the latent heat of sublimation, and w0 T 0 and w0 0v are the surface kinematics fluxes of heat and water vapor, respectively. Given the fast response (100 Hz) of the hygrometer, no correction for high‐ frequency losses in the calculation of sublimation heat fluxes was applied. Measured values of E were corrected for the effect of air density fluctuations [Webb et al., 1980] and for the interference of O2 with the rv concentration measured by the KH20 hygrometer [Campbell and Tanner, 1985; Campbell Scientific, 1993]. Considering the absolute values, the latter correction accounts for about 3.4% (median value). The atmospheric pressure used for the calculation of densities was taken from the Enea measurement station (www. climantartide.it), located at 74°41′45.3″S and 164°05′31.8″W at 91.9 m above sea level (asl). 2.3. Corrections Applied to Eddy‐Correlation Measurements of Particle Fluxes [10] The relatively long first‐order time response of the CPC means that the full atmospheric cospectrum between w and N will be undersampled at high frequencies. Therefore, it was necessary to correct the measured fluxes to take into account the incomplete coverage of the spectra. An estimation of flux attenuation was proposed by Horst [1997], who used an analytical formula based on the expected shape of the cospectra between vertical wind speed and concentration and, specifically, based on the normalized frequency at which the maximum of the cospectra are located under different stability conditions. The evaluation of the Horst [1997] cor-

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rection factor, which is particularly relevant under stable conditions, for the present data set gives an average correction of about 97% of the measured flux values, with 34% of cases having a correction larger than 100%. The average correction is calculated as the average of the corrections obtained for each 30 min period. However, this method of correction appears to give an overestimation for this specific data set. To verify the applicability of this formula to the present data set, the cospectra CwT( f ) between vertical wind velocity and sonic temperature and the cospectra Cwrv( f ) between vertical wind velocity and water vapor concentration rv were analyzed for hourly averages, as a function of the stability parameter z/L, where L is the Monin‐Obukhov length, f is the natural frequency, and z is the height of the measurements. The frequency fmax at which the maximum CwT is reached and the corresponding frequency relative to the maximum Cwrv are well correlated (Pearson correlation coefficient = 0.95). In average terms, such frequencies were found to be lower than values assumed byn Horst [1997]. This suggests that application of the corrections described by Horst [1997] will effectively lead to an overestimation of the flux attenuation correction when applied to this data set. However, the scatter in the positions of cospectral maxima is quite large (especially under stable conditions at low energy fluxes), and it is not reasonable to use the measured position of the maxima to correct for each 30 minute interval in which fluxes are evaluated. Thus an alternative method was developed based entirely on postprocessing. The method used a low‐pass digital filter (first‐order Butterworth) approximating the CPC response to a concentration step measured in the laboratory. The correction of high‐frequency losses calculated using a filter applied to high‐frequency measured time series (like sonic temperature and water vapor concentration) was used for CO2 fluxes by Goulden et al. [1997]. However, this method has never been applied to aerosol flux measurements. Measurements of sonic temperature T and water vapor concentration rv were filtered to calculate the fluxes, (w0 T 0 )filtered and (w0 0v )filtered. These fluxes were used to evaluate the ratios, aT = (w0 T 0 )filtered/(w0 T 0 ) and av = (w0 0v )filtered/(w0 0v ). Assuming a similarity between the high‐ frequency content of the fluxes of different scalars, each ratio potentially represents the fraction of aerosol flux that is lost owing to the undersampling of the high‐frequency contribution. To limit the uncertainty the two ratios aT and av were averaged to find the final ratio a representing the losses of high‐frequency contribution in the measured aerosol fluxes. A comparison of aT and av gave information regarding the uncertainty in the correction factor. This was because the main uncertainty in the correction of the high‐frequency losses was due to the assumption that w0 N 0 had a behavior similar, in terms of high‐frequency content, to that of w0 T 0 and to w0 0v . In the present data set the average ratios are aT = 0.732 and aV = 0.766, with an average difference between them of 5% (median difference = 3.5%). Therefore ±5% could be considered an average potential estimation of the residual error in the correction of high‐frequency losses. Results indicate an average effect of the correction, on measured particle fluxes, of 43%, with 11% of the data requiring a correction larger than 100%. [11] Figure 4 shows some examples of cospectra reported using the nondimensional frequency n = fz/U, where U is the

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average wind velocity in the period chosen. The cospectra were calculated over 30 minand averaged for 1.5 h. The cospectra CwN, between vertical wind velocity and particle number concentration, is normalized with the correlation w0 N 0 and a similar normalization is used for sonic temperature cospectra CwT and for water vapor cospectra Cwrv. In Figure 4a the cospectra CwN and CwT for 28 December 2006 are compared between 16:08 and 17:38 at the relatively low average wind velocity of 1.7 m/s. In Figure 4b the cospectra CwN and Cwrv for 20 December 2006 are compared between 12:49 and 13:29 at an average wind velocity of 5.1 m/s. In Figure 4c the cospectra CwT and Cwrv are compared in the period between 15 December 2006 at 23:45 and 16 December 2006 at 01:15. The results indicate that that the maximum contribution to the correlation between w and N is generally at normalized frequencies in the interval 0.1–0.5. Therefore, the system used was generally able to measure concentration fluctuations at frequencies that made a substantial contribution to the vertical turbulent fluxes of particles. [12] The turbulent particle fluxes measured using the CPC are subject to the influence of fluctuations in air density related to fluctuations in temperature and water vapor concentration. Therefore, it is necessary to apply the correction proposed by Webb et al. [1980]: DFN 1 ¼ w0 0v ; V d a FN

ð2Þ

where m = Ma/Mv is the ratio of molar masses of dry air and water vapor, and ra is the density of dry air. Equation (2) was obtained neglecting the fluctuations in temperature, which are strongly dampened in the sampling inlet [Buzorius et al., 2000]. Data reported here were corrected using equation (2), and considering its absolute value, the correction accounts for about 3% on average. [13] A further factor that requires consideration when using a CPC and the EC method to measure particle number fluxes is the possible effect of fluctuations in the saturation ratio S, which may be correlated with vertical wind speed [Fairall, 1984; Kowalski, 2001; Vong et al., 2004]. An increase or decrease in S will cause hygroscopic aerosols to grow or shrink in size, respectively. If such growth or evaporation is significant and occurs on times cales similar to those of the ambient vertical velocity fluctuations, then this could result in artificial correlations with vertical wind speed, since a fraction of the particle size distribution will move outside (or inside) the detectable size range of the CPC. The potential error induced on the deposition velocity, DVd, by this effect may be evaluated following the approach suggested by Kowalski [2001]: DVd ¼

Figure 4. Examples of cospectra. (a) Comparison of normalized CwT and CwN for 28 December between 16:08 and 17:38. (b) Comparison of normalized CwT and Cwrv for 20 December between 12:49 and 13:29. (c) Comparison of normalized CwT and Cwrv between 15 December at 23:45 and 16 December at 01:15.

kf

2

3ð1 SÞ þ 3Kf ð1 SÞ

w0 S 0 :

ð3Þ

Equation (3) is obtained considering the Junge law for the size distribution, and b is the corresponding coefficient, usually assumed to be equal to 3. The term w0 S 0 is the vertical flux of the saturation ratio and kf is a constant that depends on the chemical composition of the particle, often taken to be equal to 0.5 [Fairall, 1984; Pryor et al., 2007]. The flux w0 S 0 can be evaluated from the measurements of sensible and sublimation heat fluxes [Kowalski, 2001]. It is

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Figure 5. Temporal trend of (a) wind velocity, (b) wind direction, (c) air temperature, and (d) relative humidity, for the entire measurement period. noteworthy that deliquescence is related not only to relative humidity, but also to the composition and size of the aerosol. The present data set gives no detailed information on aerosol composition, so it is not possible to calculate an appropriate

growth factor. Therefore, the error in equation (3) is only a potential error rather than an actual error. The correction reported in equation (3) was not applied to the present data set because, as shown later, the size distribution of mea-

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negative, with an average value of −5 W/m2, whereas the sublimation heat flux was mainly positive, with an average of about 21 W/m2. Measurements are dominated by relatively extended periods with small energy fluxes (4 m/s) and turbulence intensities, as shown in Figure 7c. Under such conditions the sensible heat fluxes are negative, indicating energy moving toward the surface, and water vapor fluxes are positive, indicating an emission from the surface. This is consistent with observations performed in other measurement campaigns in Antarctica [Van As et al., 2005; Van den Broeke et al., 2005], in the Arctic [Georgiadis et al., 2000], and, specifically, on the Nansen Ice Sheet [Ferrarese et al., 1998]. between wind velocity U and [16] The measured ratio pffiffiffiffiffiffiffiffiffiffiffiffi friction velocity u* = w0 u0 was used to evaluate the average roughness height zo, for the site analyzed using a parameteriszation based on similarity theory [Stull, 1988]. The results gave zo = 0.2 ± 0.1 mm. Figure 6. The wind rose for the entire measurement period. sured particles has a main mode at about 60–70 nm, so that particle growth or shrinkage will not severely influence the ability of the CPC to count the particles efficiently. [14] The random statistical particle counting errors in the CPC will also generate a random error in the calculated fluxes. This error can be estimated, assuming random Poissonian counting statistics, using the formula derived by Fairall [1984]: w DVd ¼ pffiffiffi ; P

ð4Þ

where sw is the standard deviation of the wind vertical component and P is the average particle number counted in the time interval in which the fluxes have been evaluated. The average statistical error in the measurements reported here was about 9%.

3. Results and Discussion 3.1. Site Meteorology and Micrometeorology [15] The wind velocity was measured by the ultrasonic anemometer at a height of 12.5 m and averaged over the same half‐hour period as was the aerosol flux. During the campaign the wind velocity was relatively high, up to 15 m/s (Figure 5a), the average temperature varied between about 1° and −12°C (Figure 5c), and the average relative humidity varied between 31% and 95% (Figure 5d). The meteorology of the measurement site is characterized by episodes of strong katabatic wind blowing from the Antarctic Plateau through Reeves glacier and Priestly glacier (mesoscale circulation) associated with northwesterly (NW) directions. The predominant wind directions at the site are southeasterly and north northwesterly (N‐NW), as shown in Figure 6. Winds blowing from the N‐NW sector are the strongest, having an average speed of about 5.4 m/s, compared to the mean speed of 2.2 m/s of winds coming from the SE sector. The sensible and sublimation heat fluxes are shown in Figure 7. Over the whole measurement period the sensible heat flux was mainly

3.2. Particle Concentration, Size Distribution, and Deposition Velocity [17] Anthropogenic sources (electricity generator and emissions of the Italian base) that could potentially contaminate the measurements were all located within the same wind sector (90°–250°) with respect to the micrometeorological tower. During the measurement campaign the tower was upwind of the potential contamination sources for 41% of the time. In addition, periods were identified, accounting for 13% of the total measurement period, when low wind speeds occurred (4 m/s) shows that, in average terms, the contribution of the first mode falls to less than 8% of the total, so that the size distribution could essentially be described by a single mode with CMD = 66 nm (sg = 1.66). This is the main reason why the described previously effect of deliquescence on the measured particle fluxes can be neglected. Since the vast majority of particles have a diameter of about 60–70 nm,

any growth or evaporation, assuming typical composition and growth factors [Fitzgerald, 1975; Businger, 1986; Fairall, 1984], due to fluctuations in relative humidity will not alter the size significantly to affect the CPC counting efficiency. [20] A bimodal shape was observed in almost all observations in the analysis by Ito [1993], who reported a first mode in the sub‐10 nm range and a second mode at larger sizes. The important finding of Ito [1993] is that phenomena related to photochemical production and/or growth of particles were clearly observed. In the measurement (in Antarctica

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Figure 9. (a) Average size distribution for selected cases (uncontaminated air). (b) Average size distribution with additional selection for wind velocity higher than 4 m/s. at 2841 m asl) discussed by Park et al. [2004], related to the Investigation of Sulfur Chemistry in the Antarctic Atmosphere program, a background size distribution with a mean size of between 50 and 70 nm was observed, in good agreement with the position of the second mode shown in Figure 9. Park et al. [2004] occasionally observed a nucleation mode in the sub‐10 nm range, suggesting the possibility of cases of growth of particles due to long‐range transport. Koponen et al. [2003], in their analysis of size distribution at Queen Maud Land (Antarctica), highlighted the presence of an Aitken mode peaking between 30 and 50 nm and the presence of nucleation modes. Specifically, in some cases two nucleation modes were observed: one in the sub‐10 nm range and the second peaking between 15 nm and 20 nm. Koponen et al. [2003] reported the evidence of recent new particle formation with subsequent particle growth up to about 40 nm. However, the observed nucleation modes were associated with air masses from the sea, while no evidence was found of nucleation associated with air masses coming from the interior of the continent. Instead, the Aitken mode was present in all distributions. [21] In the data set analyzed here it is not possible to observe production of new particles in the size range of a few nanometers because the first DMPS channel is at about 11 nm. However, it is possible that the first mode shown in Figure 9 is the result of the growth of particles of a smaller radius originating from nucleation or biogenic emissions. It has been observed that the first mode is mainly important at a low wind velocity and a direction associated with air masses coming from the continental interior (between west

and northwest). Under such conditions a higher than average relative humidity (60%–70%) is usually observed, which would be compatible with particle growth due to condensation. [22] Another possibility is the mixing of different flows. In the mentioned wind direction sector, it is possible that different flows coming from different glaciers become mixed because of the channeling effects of orography. Argentini et al. [1992], studying the Nansen Ice Sheet, observed the mixing of flows coming from the Priestley glacier and from the Reeves glacier, with significant differences in temperature. Generally, the temperature of the air masses from Reeves was 2° higher than that of air masses from Priestley. The mixing of air masses of different temperature (and relative humidity) could favor condensation phenomena and the consequent growth of particles. This could provoke size distributions with two different modes associated with different thermodynamic conditions caused by the channeling of orography. Measured concentrations and deposition velocities are summarized in Table 1 for all available measurements, separating the cases of positive Vd (i.e., downward fluxes corresponding to 62% of cases), and negative Vd (i.e. upward fluxes corresponding to 38% of cases). In general terms, the upward and downward fluxes are of the same order of magnitude. The observed average value of Vd is 0.47 mm/s (median, 0.19 mm/s; interquartile range = −0.21 to 0.88 mm/s). Measurements reported by Duann et al. [1988] gave an average Vd = 0.34 ± 0.14 mm/s for particles in the size range between 0.15 and 0.5 mm. Measurements on ice surfaces (Arctic) by Nilsson and Rannik [2001] showed, for all particles larger than 10 nm, an average Vd over smooth ice of

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Figure 10. (a) Deposition velocity as a function of u*. (b) Particle number concentration versus u*. Horizontal bars represent the intervals of u* used as bins for averaging the data. Vertical bars represent the interquartile range (first and third quartile). Filled squares are average values, open squares are median values, and triangles are the number of available data. 0.26 mm/s and an average Vd over rough ice of 0.56 mm/s. The observed interval of Vd was between 0.09 and 2.3 mm/s. Nilsson and Rannik [2001] also reported an analysis separating the nucleation mode, having an average Vd of 1.4 mm/s, from the Aitken mode (with a size distribution peaking at about 60–70 nm), having an average Vd equal to 0.51 mm/s. This value is in good agreement with the results reported here, considering that the size distribution measurements show a dominant mode at about 60–70 nm. Gronlund et al. [2002] reported a median Vd of about 3.3 mm/s (and an interval between 0.8 and 18.9 mm/s) over ice, with a roughness height of about 1 mm for all particles larger than 10 nm. This is a value significantly larger than that observed in the present data set. [23] Although there is likely to be a dependence of Vd on particle size [Nilsson and Rannik, 2001], the present data set is dominated by particles of about 60–70 nm and does not gives sufficient statistics to analyze any eventual dependence of this type. The deposition velocity was segregated as a function of the friction velocity to investigate any relationship between the two. Friction velocity intervals were selected to optimize the number of data points within each interval and, hence, provide a statistically reliable median deposition velocity. The results are shown in Figure 10a, where the horizontal bars represent the intervals in friction velocity and the vertical bars represent the interquartile range of the deposition velocity within the specific interval of u*. Figure 10a reports

both the average and the median values of Vd. There is an increase in average deposition velocity at higher friction velocities, which is consistent with the observations over sea ice of Nilsson and Rannik [2001]. This correlation suggests that a reasonable normalization of the deposition velocity is the ratio between Vd and u*. This is summarized in Table 1, where the median ratio found for z/L ≥ 0 and u* > 0.05 m/s is 0.0027. This must be compared with the results reported over snow surface by Duann et al. [1988], who found an average ratio of 0.006 for particles with a diameter between 0.15 and 0.5 mm and of 0.0024 for particles with a diameter between 0.5 and 1.0 mm. It is interesting to observe that the median value of the ratio Vd/u* is almost equal to the value reported by Duann et al. [1988], if the processing is performed only on downward fluxes. [24] The correlation between Vd and u* shows that Vd is larger, on average, at high wind velocity, during the strong katabatic winds associated with air masses coming from the interior of the continent. Data were analyzed separating cases at wind velocities lower than 4 m/s (57% of data) from cases with higher wind velocities (43% of data). The deposition velocity at a low wind velocity is characterized by an average of 0.18 m/s (median, 0.13 mm/s; standard deviation, 1.2 mm/s; interquartile ratio, between −0.14 and 0.5 mm/s). In contrast, the deposition velocity at high wind velocities is characterized by an average value of 0.86 mm/s (median, 0.52 mm/s; standard deviation, 4.3 mm/s; interquartile ratio, between −0.5 and 1.6 mm/s). The median value of the ratio Vd/u* also changed with wind velocity, passing from 0.0021 for a wind velocity higher than 4 m/s up to 0.0035 for a wind velocity lower than 4 m/s. The change in the ratio Vd/u* means that the relationship between Vd and u* is not linear. However, it is interesting to observe that the median values of the ratio Vd/u* are almost constant with wind velocity when only downward fluxes are considered. [25] Figure 10b summarizes the correlation between number concentration and friction velocity in the same intervals of u* used in Figure 10a. Figure 10b also reports inforTable 1. Summary of Concentration and Deposition Velocity Statistics for Three Cases: Only Upward Fluxes, Only Downward Fluxes, and All Dataa C (cm−3) Mean SD Median IQR n samples Mean SD Median IQR n samples Mean SD Median IQR n samples

Vd (mm/s)

All Available Data 1338 0.47 1185 2.9 978 0.19 435 to 1854 −0.21 to 0.88 290 290 Only Downward Fluxes 1211 1.54 1028 2.91 892 0.65 412 to 1743 0.25 to 1.62 180 180 Only Upward Fluxes 1545 −1.28 1387 2.00 1148 −0.36 507 to 2066 −1.51 to −0.17 110 110

Vd /u* (×10−3) 3.3 10.8 2.7 −2.1 to 7.3 161 8.5 8.5 5.9 2.8 to 11.5 105 −6.4 7.4 −3.7 −7.1 to −2.0 56

a IQR, interquartile ratio; n, number; SD, standard deviation. The ratio Vd /u* is evaluated considering only cases with L ≥ 0 and u* ≥ 0.05 m/s.

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Figure 11. Probability density function of z/L. Solid vertical lines represent the zone of neutral and quasi‐neutral conditions in which the average hVdi is 0.43 ± 2.7 mm/s. The indicated intervals for hVdi represent 1 standard deviation. mation regarding the number of data (half‐hours available in each interval). The results show particle number concentration decreasing strongly with increasing friction velocity (and wind speed). This would be expected under conditions where background aerosol concentrations remain in quasi‐ equilibrium between aerosol sources (nonsurface) and sinks, with increasing wind speed leading to dilution in a regular manner. [26] Figure 11 shows the probability density distribution of the stability (z/L) for the 290 flux periods. Neutral and quasi‐neutral conditions (i.e., ∣z/L∣ < 0.2) represent 26% of the data. In contrast, unstable conditions (i.e., z/L < −0.2) represent 23% of the data, and stable conditions (i.e., z/L > 0.2) represent 51%. The average deposition velocity is essentially zero under unstable conditions (average Vd = −0.15 mm/s, standard deviation = 1.4 mm/s) but increases through quasi‐neutral conditions (average Vd = 0.43 mm/s, standard deviation = 2.7 mm/s) to stable conditions (average Vd = 0.79 mm/s, standard deviation = 3.5 mm/s). This means that upward fluxes are more important, on average, under the unstable conditions often associated with relatively low wind velocities. [27] The deposition velocity could be described in terms of a series of resistances [Chamberlain, 1983; Seinfeld and Pandis, 1998]: Vd ¼

1 ; ra þ rb þ rs

ð5Þ

where the gravitational settling is neglected, as it is not relevant for fine particles. The term ra is the aerodynamic resistance at the transfer of material between the measurement height and the roughness height, rb is the resistance of the quasi‐laminar layer enveloping the surface elements, and rs is the surface resistance to uptake of particles reaching the

surface. Since resuspension and bouncing of fine particles on this kind of surface can be assumed to be negligible, surface resistance should be 0. The aerodynamic resistance can be evaluated as a function of stability and friction velocity, following Seinfeld and Pandis [1998]. The median value of ra at a wind velocity higher than 4 m/s is 0.12 s/mm, significantly lower than the inverse of the deposition velocity. This means that at a high wind velocity the aerodynamics resistance is negligible and the surface deposition velocity Vds, defined as the inverse of the sublayer resistance rb, is almost equal to the deposition velocity Vd. However, at a low wind velocity the value of ra increases and is not negligible with respect to the sublayer resistance.

4. Conclusions [28] In this work an analysis of particle number concentrations, size distributions, and deposition velocities over ice (in some periods snow covered ice) surface in a remote site (Nansen Ice Sheet) in Antarctica has been presented. Additional measurements of local micrometeorology, including energy fluxes, were made and are discussed in relation to particle dynamics. Measurements have been taken with the EC technique using a micrometeorological system at a height of 12 m, coupled with a CPC. Use was also made of a DMPS that analyzes samples of air taken at a height of about 2.5 m. [29] Analysis of the cospectra between the vertical wind velocity and two scalar quantities (i.e., sonic temperature and water vapor concentration) showed that the correction for the limited time response of the CPC to measured fluxes can be overestimated if the formulation of Horst [1997] is directly applied. Therefore, an alternative correction method based on digital filtering of data in postprocessing was applied, which does not require a priori knowledge of the

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shape of the cospectra and could potentially also be used at other experimental sites. [30] The results indicate that the size distribution of particles can be reasonably described using two modes, and the most important mode, representing between 70% and 90% of the total number, presents a CMD of about 60–70 nm. The second mode, with a CMD of about 14–15 nm, is also present, but it is important mainly at low wind velocities and tends to disappear during strong katabatic winds. [31] The average deposition velocity is 0.47 mm/s, with 62% of cases presenting negative vertical fluxes (i.e., deposition) and 38% positive vertical fluxes. The strongest depositions are observed, on average, under stable and quasi‐ neutral conditions (together representing 77% of the half‐ hour samples), while the average deposition under unstable conditions (23% of the analyzed data) is basically negligible (presenting a negative average and a median value of 0). [32] The observed deposition velocity increases, on average, when the friction velocity u* increases. The correlation found between deposition velocity and friction velocity implies a correlation between Vd and wind speed, since the friction velocity is well correlated with the wind velocity. Specifically, the strongest depositions are observed during strong katabatic winds (wind velocities higher than 4 m/s). [33] The median value of the ratioVd/u*, evaluated for z/L ≥ 0 and u* > 0.05 m/s, is 0.0027. [34] The observed size distribution show a bimodal shape, with the first mode centered around 15–20 nm and the second mode (the dominant one) centered at about 60–70 nm. At a high wind velocity during katabatic winds the size distributions are dominated by the 60–70 nm mode. [35] Acknowledgments. The contribution of the PNRA (Programma Nazionale di Ricerca in Antartide) through project 6.7/2004 is gratefully acknowledged. The authors wish to thank Mr. G. Trivellone (ISAC‐ CNR) for his technical help in preparing the campaign, as well as the ENEA and PNRA for provision of meteorological data from their weather stations.

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