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Climate-relevant modification of the aerosol size distribution by processes associated with orographic clouds
Atmospheric Research 50 Ž1999. 241–263
Climate-relevant modification of the aerosol size distribution by processes associated with orographic clouds W. Birmili b
a,)
, B. Yuskiewicz a , A. Wiedensohler a , F. Stratmann a , T.W. Choularton b, K.N. Bower b
a Institute for Tropospheric Research, Permoserstr. 15, D-04318 Leipzig, Germany UniÕersity of Manchester Institute of Science and Technology (UMIST), SackÕille Street, P.O. Box 88, Manchester M60 1QD, UK
Abstract Cloud processes can modify optical properties of aerosol particles. As aerosols have been recognized to play an important role in the earth’s radiation budget, the understanding of climate changes is also linked to cloud processes. During a field experiment at Great Dun Fell, Northern England in 1995, experimental evidence was found for the processing of aerosol by orographic clouds. During two periods ŽMarch 31, and April 3, 1995., a shift in the particle size distribution was detected when comparing data from upwind and downwind stations. For two periods of 1 and 3 h, when the shift was pronounced, the mass increase due to cloud processing was estimated to be 1.2 mg my3 Ž"20%. and 1.7 mg my3 Ž"50%.. This equals roughly a quarter of the pre-existing submicron aerosol mass. As a major source of particulate matter, liquid-phase oxidation of sulphur dioxide was identified. Modelling results from Bradbury et al. wBradbury, C., Bower, K.N., Choularton, T.W., Swietlicki, E., Birmili, W., Wiedensohler, A., Yuskiewicz, B., Berner, A., Dusek, U., Dore, C.-J., McFayden, G.G., 1999. Modelling of aerosol modification resulting from passage through a hill cap cloud.x strongly support such a reaction mechanism. Furthermore, large amounts of ultrafine particles were observed downwind the mountain ridge with almost none present at the upwind and summit sites. Some observations suggest that HCl may have degassed from the droplets when the cloud was evaporating. Another factor increasing the nucleation probability could have been the aerosol surface area which decreased by 35% prior to the occurrence of ultrafine particles. q 1999 Elsevier Science B.V. All rights reserved. Keywords: Cloud processes; Gas-to-particle conversion; New particle formation; Sulphate production; Cap cloud; DMPS
)
Corresponding author
0169-8095r99r$ - see front matter q 1999 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 9 - 8 0 9 5 Ž 9 8 . 0 0 1 0 6 - 9
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1. Introduction Aerosols are believed to play an important role for the earth’s radiation budget, and thus for climate. Two principal effects of this so-called whitehouse effect ŽSchwartz, 1996. have been recognized. The first is that airborne particles scatter part of the incident solar shortwave radiation back to space Ždirect effect of radiative forcing.. Particles of the Aitken and accumulation mode aerosol Ždry diameter: 0.05–1.0 mm., which represent the overwhelming fraction of particulate number concentration, scatter sunlight the more effectively the larger they are in optical diameter. This is important from the point of view that Aitken and accumulation mode particles are able to increase their size by in-cloud formation of sulphate during their activation as cloud condensation nuclei ŽLelieveld and Heintzenberg, 1992.. As a second effect, an increased aerosol particle number may raise the reflectivity of clouds Žindirect radiative forcing.. Ultrafine aerosol particles are produced by gas-to-particle conversion, and grow by coagulation and further condensation of condensable vapours Že.g., sulphuric acid, nitric acid, organic vapours, etc... This process may increase the number of Aitken and accumulation mode particles. If then a cloud is formed, more particles might be activated to cloud droplets. Consequently, the average cloud droplet size will be smaller compared to a situation involving lower particle numbers. With constant liquid water content, the cloud albedo may be increased due to a higher optical activity of smaller cloud droplets. Both the indirect and the direct radiative forcing lead to a net cooling of the earth’s surface, and thus are able to partially offset the greenhouse effect. This study investigates two climate-relevant effects that cloud processes might induce. Ž1. Increase of aerosol particles in size after their passage through a cloud due to aqueous phase chemical reactions in cloud droplets. Several works ŽHegg, 1985; Chameides and Stelson, 1992. report that the in-cloud oxidation of sulphur in the atmosphere constitutes a major pathway for transferring mass from the gas phase to the particulate phase. This has also been demonstrated recently by cloud chamber experiments ŽHoppel et al., 1994.. The basic mechanism is that cloud droplets take up soluble sulphur dioxide ŽSO 2 . which is then oxidised in the liquid phase to sulphate ŽSO42y . under the consumption of either H 2 O 2 or O 3 ŽHegg, 1989.. In acidic droplets Ž- pH 6., H 2 O 2 is recognized as the major oxidant, whereas above pH 6, ozone becomes more relevant. For the latter oxidation process, the presence of ammonia is required. As a result of the additional ionic matter formed in the liquid phase, the particle may be larger in diameter after the cloud passage. As a consequence, the optical properties of the particles change along with the change in size. Especially Aitken and accumulation mode particles become optically more efficient as they grow, and thus, effect visibility and radiative forcing. The latter aspect is expanded in a separate paper ŽYuskiewicz et al., 1999. based on the measurements of this paper. Only few field experiments have been reported which quantified a change in the size distribution due to cloud processing. Alkezweeny Ž1995. report indications of particle growth after an air parcel had passed through a summer cumulus cloud.
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Ž2. Production of new ultrafine aerosol in association with clouds. On the one hand, aerosol particles are removed from the atmosphere by processes like in-cloud scavenging, below-cloud scavenging, and dry deposition; on the other hand, the atmospheric aerosol budget is being supplied with new particles by direct particulate emission, and by homogeneous nucleation of new particles from the gas phase, the latter of which contributes especially to produce new relevant numbers of new particles. Fresh aerosol particles with diameters smaller than 10 nm may nucleate if gaseous precursor species are available locally in the atmosphere at supersaturation. The most important of these species has been recognized to be sulphuric acid ŽH 2 SO4 . together with water vapour. Sulphuric acid is formed in the atmosphere by gas-phase oxidation of sulphur dioxide ŽSO 2 . in the presence of hydroxyl ŽOH. radicals ŽRaes et al., 1992; Easter and Peters, 1994.. The nucleation process depends strongly on factors such as temperature, partial pressure of condensable material and the surface area of pre-existing particles ŽWarren and Seinfeld, 1985; Jaecker-Voirol and Mirabel, 1989.. Existing nucleation theories, however, predict nucleation rates that differ by orders of magnitudes ŽGirshick et al., 1990.. Nucleation rates observed in the atmosphere differ from theoretically predicted values by similar amounts ŽWeber et al., 1995.. One reason might be that fundamental thermodynamic parameters Že.g., vapour pressures. are not known with suitable accuracy. Another is that in the atmosphere, additional species are likely to be involved in nucleation processes Že.g., NH 3 , HCl, HNO 3 .. A number of field experiments report observations of ultrafine particles in the outflow of clouds ŽHoppel et al., 1994; Wiedensohler et al., 1997.. Saxena Ž1996. found increased aerosol number concentrations just after clouds had been dissipating at Palmer Station, Antarctica—an observation which could have been caused by new particle formation.
2. Field experiment A field experiment was carried out in Great Dun Fell ŽNorthern England. in spring 1995, where an orographic cloud was formed on a mountain ridge. This cloud reactor served to investigate the influence of a cloud on the aerosol size distribution with emphasis being directed towards detecting small changes during the passage. Four Differential Mobility Particle Sizers ŽDMPS. were operated at the sites of Fell Gate Župwind., Mine Road Župwind, near cloud base., Summit, and Moor House Ždownwind.. Other physical, chemical and meteorological measurements provided an extensive dataset, which yield to a better understanding of cloud processes and their implications. The lead article of this field experiment ŽBower et al., 1999. gives an overview of the Great Dun Fell experiment 1995 and its basic results.
3. Instrumental Four Differential Mobility Particle Sizers ŽDMPS. were used to determine particle size distributions. Each system consists of two Hauke-type Differential Mobility Analy-
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sers ŽDMAs. —therefore called a Twin DMPS system. A DMA basically segregates aerosol particles according to their electrical mobility which is transferred to a size distribution after. Technically, the DMAs follow the design of Winklmayr et al. Ž1991. ŽDMA type 3r150. with variations in the exact dimensions. In particular, two DMAs with different center rod lengths were used to measure different particle size ranges Žcf. Table 1 for technical specifications and flow rates of the DMAs.. These are denoted as ‘UDMA’ Žshort centre rod., and as ‘DMA’ Žlong centre rod. in the following. A Condensation Particle Counter CPC Žmodel 3010; TSI, St. Paul, MN. counted aerosol particles downstream of the DMA, whereas a UCPC Žmodel 3025, TSI. counted for the UDMA. At all measurement sites, impactors Žcut-off size: 3 mm at ambient conditions. were mounted on masts Žheight: 4 m. and provided interstitial aerosol samples. To insure that the particle size measured refers to the dry size of the particles, the sheath air supplying the DMAs was dried at ambient temperature before entering the laboratory caravans. At the stations Fell Gate, Summit, and Moor House, the full Twin DMPS setup ŽDMA q UDMA. was operating. At Mine Road, only one medium DMA Ž31 diameter channels in the range 22–676 nm. was used in conjunction with a UCPC 3025 because no UDMA was available for that site. All DMAs were operated in a channel-wise stepping mode. The diameter channels were evenly spaced on a logarithmic scale Ž18 channels 3.1–25 nm for the UDMA, 30 channels 25–794 nm for the DMA.. The sampling time was 15 min for an entire scan. All DMA flow rates were set by adjustable critical orifices Žneedle valves. using a bubble flow meter ŽGilibrator-2 Calibration System, Senseydyne, Clearwater, FL, USA.. 3.1. Error estimation for the DMPS technique The experimental errors connected with the measurement technique were estimated as best as possible. The following errors were quantified and accounted for in the evaluation of the final size distributions. The finite number of particles counted in each measurement bin causes a statistical error ŽPoisson error.. This is relevant in the size range 3–25 nm measured by the UDMA. The main reasons for low count numbers are the low effective sampling flow of the UCPC 3025 Ž0.03 lpm., losses of ultrafine particles due to Brownian diffusion, and the low charging efficiency of ultrafine particles. To compensate this effect at least partially, a sampling time of 45 s was selected for each diameter channel that is - 25 nm.
Table 1 Electrode length and air flow specifications for the DMAs used for this work DMA type
Center rod length Žcm.
Sheath air flow Žlpm.
Aerosol flow Žlpm.
Measured particle size range Žnm.
UDMA-Hauke short DMA-Hauke medium
11.0 28.0
20.0 5.0
2.0 0.5
3–25 25–794
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Another source of instrumental error is the use of adjustable critical orifices Žneedle valves. to regulate the DMA flow rates. The variations of the flows through such variable orifices were empirically determined to "0.7% during the field experiment. As the sheath air to aerosol flow ratio is 10:1, and two separate orifices Žsheath air q excess air. are involved, this relatively small error may sum up to "10% regarding the aerosol sample flow. Considering simple DMA transfer theory, this may falsify the concentrations measured by similar amounts. Therefore, we included the "10% error in all error bars. Important for the evaluation of the size distribution is also the knowledge of the transfer function of the DMAs, especially of the UDMA ŽBirmili et al., 1997.. As a result of particle losses due to particle diffusion in the devices, the transmission of ultrafine particles decreases strongly for small sizes Ž Dp - 10 nm for the UDMA.. Other systematic errors Žparticle losses due to diffusion in inlets, connecting tubings, charge neutralizers. are estimated to be below 5%. Another error, though difficult to estimate, occurs when the air mass sampled by the system changes a lot while the DMPS is scanning. Such data points were removed from the data set. An additional error may occur if the sheath air in a DMA is not completely dry, which can result in an overestimation of the dry particle size. This aspect is addressed later in the paper.
4. Flow connectivity The four measuring sites ŽFell Gate, Mine Road, Summit, and Moor House. are aligned along the expected flow path, however, not on an exact straight line. The distances are 1.8 km between Fell Gate and Mine Road, 1.2 km between Mine Road and Summit, and 4.7 km between Summit and Moor House. For more details of the terrain, see Bower et al. Ž1999.. For the purpose of comparing measurements between different sites, evidence must be given that the air flows continuously across the mountain ridge, and the different sites are ‘connected’. One cannot strictly prove that the same air mass was sampled at all measurement sites Žlike in an ideal Lagrangian experiment.. One can, however, assure by a number of means Žshown below. that similar streamlines of the airflow were sampled. This can be done under the assumption that the aerosol to be observed is horizontally homogeneous within a range of 1–3 km.
Table 2 Run periods for which flow connectivity was established Run period of connected flow
Fell Gate upwind Ž435 m a.s.l..
Mine Road upwind Ž680 m a.s.l..
Summit Ž845 m a.s.l..
Moor House downwind Ž560 m a.s.l..
I II III
cloud-free cloud-free cloud-free
cloud-free partly in cloud partly in cloud
cloud-free partly in cloud always in cloud
cloud-free cloud-free cloud-free
April 1, 1200–1800 h March 31, 1200–1800 h April 3, 0000–1800 h
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To establish flow connectivity, we used various data from all sites: particle size distributions, wind speed, wind direction, temperature profiles, liquid water content wmeasured by a particle volume monitor ŽPVM.x, cation concentrations of Naq, Kq, Mg 2q, and Ca2q ŽRotheroe–Mitchell impactor data, see Dore et al., 1999., and profiles of NO x Žsee Cape et al., 1999.. For the purpose of this work, three periods with evidence for flow connection were investigated Žcf. Table 2.: one event featuring cloud-free conditions, and two events with a cloud present on the mountain ridge. 4.1. Run period I (cloud-free conditions) Fig. 1 shows a measurement from April 1, 1995, 1600 h ŽMoor House 15 min later due to the travelling time of the air mass. illustrating the quality of the DMPS measuring technique. The size distributions of all stations agree very well within the instrumental error range in a wide size range Ž5–794 nm.. At the time, no cloud was on top of the ridge Žzero liquid water content at all stations.. This agreement indicates that the same air was investigated. Divergences occur only in the ultrafine range for Dp - 5 nm. Error bars, as described in the preceding text, illustrate the measurement uncertainty. To make the plot not too busy, error bars were displayed for one station only. It can be seen that for 10 - Dp - 400 nm, the overall error is fairly constant Ž"10%., mainly due to flow rate variations caused by adjustable orifices. Near the upper end of the distribution Ž Dp ) 400 nm., the statistical error increases slightly when concentrations fall short of 100 cmy3 Žd Nrdlog Dp .. Similarly, error bars increase for Dp - 10 nm due to the degrading counting statistics Žlow sampling flow of the UCPC..
Fig. 1. Dry particle size distributions during run period I.
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Meteorological observations taken from this period strongly support flow connection. The wind speed was fairly high at all sites Ž; 15 m sy1 on Summit. with wind directions at all sites being perpendicular to the ridge, and rather similar ŽFell Gate and Mine Road: ; 3008, Summit: ; 2508, Moor House: ; 2708.. Such conditions provide a steady airflow across the ridge. Dry ambient temperatures were: Fell Gate 108C Ž435 m., Moor House 9.28C Ždownwind, 560 m., Mine Road 8.28C Ž680 m., and Summit 6.08C Ž845 m.. This is consistent with the assumption that an air mass is lifted adiabatically when passing over the ridge. Following such a model, Fell Gate is ideally 4.0 K, Mine Road 1.6 K, and Moor House 2.8 K warmer than Summit. 4.2. Run period II (cloud) Fig. 2 shows the particle size distributions of all stations on March 31, 1645 h ŽMoor House 1700 h.. A good agreement in the size range 20–80 nm can be seen. In that size range, we expect no significant change of the size distribution during a cloud passage. One reason is that particles 20–80 nm are too large to coagulate efficiently with cloud droplets. They are also too small to be activated as cloud droplets. Note that a large fraction of the accumulation and Aitken mode aerosol with Dp ) 80 nm are absent at the Summit site due to in-cloud scavenging Žliquid water content ; 0.6 g cmy3 .. Also in this case, the meteorological data support the flow to be connected across the ridge. Southwesterly winds Žspeed ) 5 m sy1 . prevail at all stations Ždirections ; 2408–3108.. The temperature profiles stay well-separated with the gaps between the profiles being smaller than those derived from the adiabatic lift of an air parcel. This can be explained
Fig. 2. Dry particle size distributions during run period II.
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Table 3 Activated particle volume fractions during run periods II and III Run period
Time span
Activated particle volume fraction Ž Dp -800 nm.
Liquid water content at the Summit station Žg cmy3 .
II (March 31, 1995)
1200–1330 h 1345–1415 h 1430–1800 h
96.0"0.9% no activation 86.0"4.3%
0.2 0.0–0.1 0.0–0.8
III (April 3, 1995)
0000–1400 hr entire period
95.4"1.9%
0.2–0.5
by a nonzero liquid water content on the pathway between the stations. Some measured species Že.g., NO x , cations. are expected to be conserved during a cloud passage, and can thus be used as a tracer. An analysis of the NO x profiles ŽCape et al., 1999. shows a good correlation between all stations for period II. After subtracting an instrumental offset from the Moor House data, a linear correlation coefficient of 0.90 was determined between the NO x time histories from Fell Gate and Moor House. To obtain information about the activation of particles in the cloud, the number size distributions were transferred to volume size distributions. From these, the activated particle volume fraction was calculated from Summit Žin-cloud. and Fell Gate Žout-ofcloud. data. The results are displayed in Table 3.
Fig. 3. Dry particle size distributions during run period III.
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4.3. Run period III (cloud) Fig. 3 shows an exemplary measurement taken at 0515 h on April 3, 1995 ŽMoor House 0530 h.. We see once again a good agreement of the DMPS spectra in the size ranges where we expect it. Part of the accumulation and Aitken mode particles with Dp ) 60 nm, however, are scavenged at the Summit site Žliquid water content ; 0.2 g cmy3 .. As for run period II, the activated particle volume fractions were calculated ŽTable 3.. Another feature of the size distributions is the occurrence of large concentrations of ultrafine particles at Moor House. This feature will be discussed separately below. Also in this case, the meteorological data support strongly the assumption of connected flow during the period of concern. The wind speed at all stations remains quite stable ŽFell Gate ; 4 m sy1 the lowest, Summit ; 15 m sy1 the highest. with all stations agreeing reasonably well in a westerly wind direction. The temperature profiles remain well-separated with their differences being similar to period II. The Rotheroe– Mitchell impactor data Žcation mass concentrations. of Fell Gate and Moor House agree reasonably well indicating that the same air mass is investigated. Moreover, the NO x profiles from Fell Gate, Summit and Moor House are similar. To sum up, a large number of observations indicate that the airflow was connected during periods I–III.
5. Sulphate production in the liquid phase During periods when the airflow was connected, the size distributions of different stations were carefully compared. Size distributions as in Fig. 2 were found, when the DMPS spectrum of Moor House revealed a significant shift towards larger particle sizes in the Aitken and accumulation mode range Ž60–400 nm.. Eight such distributions were found during period II and nine during period III, respectively. A possible explanation could be the in-cloud oxidation of soluble gases as described in the introduction. Two cases, when this effect became quite obvious, will be discussed, and the effect will be quantified. To illustrate the shift in particle size distribution, the measurement points 1615, 1630, and 1645 h from March 31 Žperiod II. were averaged ŽFig. 4.. The Mine Road data is not displayed in the figure because the station changed from in-cloud to out-of-cloud several times during the period of concern. A suitable particle size interval for a quantification of the growth effect is 60–400 nm, since this is the range in which we observe significant changes in the size distribution, and the range in which error bars are small. For the interval 60–400 nm, the total particle concentration and the particle volume concentration were calculated. To avoid particle volume concentrations to be influenced by the total particle number concentration Žwithin the error range of the instruments., the particle number size distributions were normalised to the total number concentrations of Fell Gate. Thus, we make provision that only the net effect Žshift in size distribution. accounts for differences in the particle volume concentrations on both sides of the mountain ridge.
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Fig. 4. Shift in the particle size distribution between upwind and downwind station during run period II Ž1615–1645 h..
5.1. Cloud-free conditionsr run period I (April 1) No effect: during this period, little variation can be seen between the different profiles of particle volume concentration Žcf. Fig. 5.. 5.2. Shift in size distributionr run period II (March 31) During period II, particle volume concentrations from different stations agree well between 1200 and 1500 h Žcf. Fig. 6.. Afterwards, as Summit goes into cloud Žnonzero
Fig. 5. Comparison of particle volume concentrations Ž60 nm - Dp - 400 nm. at different sites for cloud-free conditions Žperiod I..
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Fig. 6. Comparison of particle volume concentrations Ž60 nm - Dp - 400 nm. at different sites for a cloud event Žperiod II.. Comparison to time histories of liquid water content and sulphur dioxide.
liquid water content., the curve of Moor House drifts upward slightly being significantly larger than Fell Gate and Mine Road between 1600 and 1700 h. Note that the curve of Mine Road drops after 1615 h because the station enters into the cloud at that time Žalso indicated by a nonzero liquid water content. with a considerable fraction of the particle volume being scavenged. Such a difference between particulate volumes on both sides of the hill regarding sulphate production is supported by Cape et al. Ž1999. who observed that droplets of the cloud took up a significant portion of SŽVI.. The excess volume at Moor House after 1600 h coincides with a slightly increasing input concentrations of SO 2 after 1600 h, as can be seen in the bottom diagram of Fig. 6. In contrast to the period 1600–1700 h, however, we see no indications of particle growth between 1200 and 1400 h. During that period, SO 2 was even higher, at a similar liquid water content of ; 0.2 g cmy3 . The levels of gaseous H 2 O 2 can neither explain the difference between both episodes, since the levels were equally low, around 0.1 ppb in both cases. By comparing the particle volume concentrations, an average difference of 0.69 mm3 cmy3 Ž"20%. could be determined using data from 1600–1645 h Žsee also Table 4.. This corresponds to an increase of the aerosol mass concentration by 1.21 mg my3 Ž"20%. assuming that the additional mass consists mainly of ammonium sulphate Ždensity 1.76.. The effect cannot be considered negligible since, if the theory of sulphate
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Run period
Time span
Measured volume shift Žmm3 cmy3 .
Corresponding mass shift Žmg my3 . a
II (March 31, 1995)
1200–1800 hr entire period 1600–1645 hr intense production
0.29
0.51
0.69
1.21
0000–1400 hr entire period 0100–0245 hr intense production
0.56
0.98
0.98 b
1.72 b
III (April 3, 1995)
a
Percentage volume increase in interval Ž0.06–0.8 mm.
Mixing ratio of SO 2 Žppb V.
Liquid water content at the Summit station Žg cmy3 .
23%
0.2–0.3
0.4–0.5
25%
0.1–0.3
0.3–0.4
Assuming the density 1.76 of ammonium sulphate. Cannot be explained entirely by liquid-phase oxidation of sulphur dioxide. See details in the text.
b
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Table 4 Calculated volume and mass shifts of the particulate aeosol during a cloud passage for two selected run periods ŽII, III.
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production holds, roughly a quarter of the particle volume Ž60–400 nm. was produced in the cloud. 5.3. Shift in size distributionr run period III On April 3, 1995, when a thick cloud enveloped the mountain ridge, we also observed a systematic shift of the particle size distribution to larger sizes in the Aitken and Accumulation mode range, similar to that of period II described above. Looking at the time histories of particle volume concentrations Žcf. Fig. 7., it seems that some continuous particle growth happened through the whole time period 0000–1400 h, although it was not very pronounced except during the episode 0100–0400 h, when the shift could be seen clearly in the size distributions. This period of a strong shift coincides with the beginning of an episode with elevated SO 2 concentrations Žcf. bottom diagram of Fig. 7. supporting the theory of particle growth by sulphate production. After 0230 h, the production rate shrinks. As one possible reason, we suspect the decreasing droplet volume available for liquid-phase reactions that results from a drop in liquid water content Žcf. diagram in the middle of Fig. 7.. During the phase of intense
Fig. 7. Comparison of particle volume concentrations Ž60 nm - Dp - 400 nm. at different sites for a cloud event Žperiod III.. Comparison to time histories of liquid water content and sulphur dioxide.
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production 0100–0245 h, the average additional volume downwind the cloud was 0.98 mm3 cmy3 corresponding to a mass shift of 1.72 mg my3 . Averages for the entire period 0000–1400 h are lower, 0.56 mm3 cmy3 and 0.98 mg my3 Žall values " 20%., respectively. Evidence for sulphate production was gathered from modelling of in-cloud sulphate production in association with orographic clouds. Details of the model and the full results are presented in Bradbury et al. Ž1999.. As an input, the model uses measured particle size distributions from Fell Gate and calculates distributions at Moor House, modified by the cloud process. Bradbury et al. found that the cloud model reproduces the trend of the real size distribution measurements at Moor House reasonably well. It must be stated, however, that the observed maximum mass shift of 1.72 mg my3 in period III cannot entirely be explained by the liquid-phase oxidation of SO 2 . The formation of a corresponding amount of ammonium sulphate would require more SO 2 Ž; 0.7 ppb V. than was actually available in the air mass upwind the cloud Ž0.2–0.4 ppb V.. Besides, no SO 2 measurements were made at Moor House, and hence, no statement can be given about SO 2 consumption during the cloud process. Besides the conversion of matter other than SO 2 to the solid phase, another effect could be responsible for the divergence between the mass shift and the observed SO 2 concentrations. This is an eventual overestimation of the dry particle size in the DMAs. Tang and Munkelwitz Ž1994. report a hysteretical behaviour, when particles are humidified to high relative humidities, and are subsequently dried. Dry ammonium bisulfate particles, as a realistic example, convert rapidly to liquid particles Ždeliquescence., and grow further, when 80% relative humidity is exceeded. After that, however, they do not reach their initial dry size unless dried to a relative humidity below 37%. In the field experiment, the first mentioned process would correspond to the humidification of the particles, as relative humidity increases, while the air parcel is ascending. Eventually, the relative humidity was below the deliquescence point of the particles at the upwind measurement station ŽFell Gate.. The second Ždrying. process takes place inside the DMAs. There, the authors assume relative humidities lower than 25%, since the sheath air was conditioned by adsorptional dryers before entering the DMAs. If the wet particles, however, need a noticeable time Ža few milliseconds. to get in equilibrium with the dry air, they will shrink to their final dry size only during the passage through the DMA, and, consequently, their dry size will be overestimated. An overestimation of the dry particle size at the downwind station ŽMoor House. of, e.g., 5% would lead to an overestimation of particle volume Žand mass. by 15%; it can be seen that the calculated mass shifts are quite sensitive to this effect. This could therefore explain the overestimation of the maximum mass shift of 1.72 mg my3 between 0100–0245 h in period III. For the discussed reasons, the value 1.72 mg my3 is assigned with an uncertainty of "50% in the conclusions of this paper.
6. Formation of ultrafine particles Special attention was also paid to the occurrence of ultrafine particles. The performance of three DMPS systems with a lower detection limit of Dp ; 3 nm ŽFell Gate,
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Summit, and Moor House. permits an intercomparison of ultrafine concentrations of the same air mass, once flow connectivity is established. During the entire measurement campaign, ultrafine particles Ž Dp - 20 nm. were observed most of the time, and frequently, in the shape of a mode. Concentrations in that size range were similar at all stations Fell Gate, Summit, and Moor House Žat Mine Road, no ultrafine particle sizer was operated.. Significant differences between different sites occurred only in the size fraction 3–8 nm. This is different from observations by Wiedensohler et al. Ž1997. who report, from a previous field experiment at the same location two years earlier, a new ultrafine mode with mode diameters of 5–15 nm in the outflow of the cloud. Fig. 8 compares upwind ŽFell Gate. and downwind ŽMoor House. concentrations of ultrafine particles Ž3–8 nm. for five periods ŽI, II, IIIa–c.. Note that period III was divided into three parts to point out the period IIIb Ž0500–0800 h. during which we report the highest concentrations of ultrafine particles at Moor House. Data from the Summit station are not displayed, since they follow closely those from Fell Gate. The integral number concentration of ultrafine particles was calculated by numerically integrating the size distributions up to Dp s 8 nm. For the noncloud period I, the concentrations on both sides of the hill nearly show a 1:1 correspondence, with a little excess at Moor House. This also holds for the cloud event II. During cloud event III, however, ultrafine concentrations at Moor House exceeded those at Fell Gate substantially between 0500–0800 h. 6.1. ObserÕations during run period III On April 3, westerly winds carried Atlantic air across Great Dun Fell. As deduced in the preceding text, the flow was connected between 0000 and 1400 h. Fig. 9 shows time
Fig. 8. Comparison of ultrafine particle concentrations Ž3–8 nm. of Fell Gate and Moor House.
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Fig. 9. Ultrafine particle concentrations, liquid water content, and sulphur dioxide during run period III featuring large concentrations of ultrafine particles at Moor House.
histories of the ultrafine concentrations at Fell Gate, and Moor House Žtop diagram. plus liquid water content Ždiagram in the middle. and sulphur dioxide Žbottom diagram..
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Aerosol surface concentration was determined from DMPS size distributions by numerical integration assuming spherical particles and is plotted in Fig. 10 Ždiagram in the
Fig. 10. Aerosol surface concentrations, temperatures, and nitrate mass concentrations during run period III.
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middle.. At the beginning and at the end of the run, ultrafine concentrations stayed below 1000 cmy3 at both stations. Between 0500 and 0800 h Žperiod IIIb., however, ultrafine concentrations downwind ŽMoor House. exceeded those at Fell Gate by factors up to 20. Ultrafine concentrations Ž3–8 nm. reached 5000 cmy3 at Moor House, whereas in the complementary size interval 8–800 nm, only ; 2000 cmy3 were found. The overwhelming number of atmospheric particles was thus within the ultrafine range. 6.2. Statistical assessment of the data points of sub-period IIIb The aim of this section is to judge whether the observed event of new particle formation stands out statistically in comparison to the rest of the periods of the field campaign. The methods we employed follow standard procedures used in statistical textbooks. As mentioned, we discern five sample periods ŽI, II, IIIa–c; cf. Table 5.. As a convenient variable to characterize excess of ultrafine particles at Moor House, we used a relative difference X of ultrafine particles between Moor House and Fell Gate defined as X s Ž NM H y NF G .rŽ NM H q NF G .. NM H and NF G are ultrafine particle concentrations Ž3–8 nm. at the two stations. The higher the value of X, the larger is the excess of ultrafine concentrations downwind. A negative X indicates higher ultrafine concentrations at Fell Gate. To account for error bars as realistically as possible, the individual error s i of each measurement point Ni was calculated from the absolute number of particles that were actually counted in the size interval 3–8 nm ŽPoisson error. plus the 10% uncertainty of the DMPS measurement. The measurement points were averaged for each of the sample periods. When calculating the sample standard deviation s X of each sample period, we considered the individual error s i as well as the deviation of each measurement point Ni
Table 5 Tests of hypotheses and significance for the occurrence of excess ultrafine particles at Moor House Sample period, time
n
X
sX
sx
Z
H0
Accept H 0?
II I IIIa IIIb IIIc
22 22 20 12 20
y0.07 0.13 0.47 0.64 0.18
0.50 0.47 0.81 0.52 0.66
0.108 0.103 0.185 0.156 0.150
y0.67 1.32 2.54 4.12 1.21
mX s 0 mX s 0 mX s 0 mX s 0 mX s 0
yes yes yes no yes
XI y XA
S X IyXA
Z
0.21 y0.33 y0.51 y0.05
0.149 0.211 0.187 0.182
1.39 y1.58 y2.72 y0.25
mI s mA mI s mA mI s mA mI s mA
yes yes no yes
April 1, 12:00–17:30 March 31, 12:00–17:45 April 3, 00:00–04:45 April 3, 05:00–08:00 April 3, 08:25–13:45
Comparison of sample periods Žperiod I vs. period A g II, IIIa–c. I Žcloud-free. vs. II I Žcloud-free. vs. IIIa I Žcloud-free. vs. IIIb I Žcloud-free. vs. IIIc
X
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from the sample mean X. To give more weight to measurement points with a small standard deviation s i , the mean values X were calculated using the inverse square root of s i as a convenient weight for each Ni . In Table 5, it can be seen that X assumes its largest values during periods IIIa and IIIb when we found the most excess of ultrafine particles downwind the cloud. In a first step, we tested whether data from any of the sample periods ŽI, II, IIIa–c. deviate from X s 0 at all. Therefore, a zero hypothesis H 0 : m X s 0 was proposed for the population of each sample period. The standardised mean Z s XrŽ s Xr6n y 1. was calculated for each sample period. For a significance level a s 0.01, H 0 is acceptable if y2.58 - Z - q2.58 Žtwo-tailed test.. In this context, 1 y a s 99% can be regarded as the probability that our zero hypothesis is true if Z is within the range as indicated below. As we can see from Table 5, the variable X deviates significantly from zero only for the sample period IIIb, since H 0 was rejected in this case, while it was accepted in all other cases. At an alternative level a s 0.05, H 0 would have been rejected for one more period: IIIa. Our next Žmore important. step is to investigate whether any of the periods II and IIIa–c Žthe case of a cloud. can be distinguished statistically from our reference sample, the cloud-free case I, where we expect no change of the ultrafine particle number across the hill. Hereto, the differences between the variables X I Žperiod I. and XA Žperiod A g II, IIa–c. and their corresponding standardised means ZX were calculated Žfour bottom rows of Table 5.. The new zero hypothesis was that the means of the two periods agree Ž m I s m A . leading to similar results: again for period IIIb, H 0 was rejected, while it was acceptable for all other cases. This means that within a probability of 99%, the samples taken during period IIIb were different from those during the cloud-free period I and can be considered a unique part of the dataset. 6.3. Exclusion of entrainment; discussion A detailed meteorological analysis yields no signs of entrainment of air into the cap cloud, suggesting that ultrafine particles were produced in the airflow downwind. If there was entrainment of dry air from aloft ŽKelvin–Helmholtz instabilities., the liquid water content on Summit should be lower than suggested by an adiabatic lift model. Such a model estimates the increase of liquid water content ŽLWC. with height to 0.10 g cmy3 per 50 m ascent. Fig. 9 Žmiddle. shows an LWC of 0.15 g cmy3 at Mine Road Ž680 m., and 0.5 g cmy3 at Summit Ž845 m. which matches the calculated LWC difference of 0.33 g cmy3 . This is the case between 0100–0300 h, and 0900–1030 h. Between these times Žwhen ultrafine particles were observed., this calculation cannot be carried out, since Mine Road was out of cloud Žzero LWC.. The temperature difference between both stations, however, remains fairly constant through the run indicating that no much atmospheric change happened between Mine Road and Summit. The cloud base most likely stayed just above Mine Road during the time when ultrafine particles were observed. This is also indicated by the small spikes in the LWC profile of Mine Road when the cloud base touches the station. It is thus probable that the observed large concentrations of ultrafine particles were produced in the air flow downwind. A further
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argument for particle nucleation shortly before the measurement on April 3, 1995 is the fact that the particles appear only in the size range between 3 and 8 nm, near the lower detection limit of the system. The concentration of SO 2 , the most important precursor for H 2 SO4 , had its maximum a few hours before the ultrafine particle event, between 0200–0400 h. During the actual event Ž0500–0800 h., the SO 2 level was comparably low, near 0.1 ppb V. Moreover, at that early time of day Žsunrise 0530 h., there was no or only very little incident solar radiation that could have generated a significant amount of hydroxyl ŽOH. radicals, which is the preferred oxidant for SO 2 . These facts suggest that also nucleation mechanisms other than binary H 2 SO4rH 2 O nucleation were relevant for the formation of the observed ultrafine particles. An alternative that merits a discussion in the context of this field experiment is the formation of ammonium chloride particles, which was theoretically investigated by Korhonen et al. Ž1997.. The latter authors say, on the basis of model calculations, that it is highly improbable for ammonia and hydrochloric acid to nucleate under dry atmospheric conditions. If, however, high relative humidities and low temperatures are attained like in the case of an evaporating cloud, such nucleation is considered possible to take place in the atmosphere. This is the result of an improved nucleation rate calculation, which takes hydrate interactions into account. Ammonia, the first precursor of ammonium chloride aerosol, was measured at Moor House with an AMANDA system Žconductivity measurement.; ammonia concentrations were constantly low, but nonzero Ž; 0.3 mg my3 . between April 2, 2200 h, and April 3, 1000 h, which includes the nucleation event, and the preceding 7–8 h. The second reaction partner, hydrochloric acid was not measured directly in this field experiment. From laboratory experiments, however, it is known that hydrochloric acid can gas-out from liquid droplets under conditions like in a dissipating cloud Žten Brink and Spoelstra, 1996.. Assuming that both HCl and HNO 3 are resolved in a cloud droplet, nitrate tends to remain with the droplets, while gaseous hydrochloric acid is expelled, when the droplet size decreases during cloud evaporation. This reaction requires a significant fraction of the aerosol to consist of sea-salt, which is likely to be the case for the investigated air mass, originating from the Atlantic. Additional support for the theory of outgassing HCl results from the trend of ionic nitrate mass concentrations measured during the experiment by Berner impactors Žcf. the overview paper by Bower et al., 1999.. Deviations between the stations of Fell Gate and Moor House occurred only in the largest impactor stage Ž1.6–5.1 mm aerodynamic diameter. which accumulates roughly 75% of the particulate mass for Dp - 5.1 mm. It was observed that, along with a change in air mass after 0400 h, the nitrate concentrations at Moor House exceeded those at Fell Gate after 0600 h though before, the reverse was the case. This could be interpreted as an enhanced attachment of nitrate to the largest aerosol particles as a result of the above reaction Ždisplacement of HCl; residence of nitrate. during the cloud passage. Using the suggestions of Korhonen et al. Ž1997., however, the occurrence of ultrafine particles in this experiment can, however, still not be satisfactorily explained by the ammonia and hydrochloric acid nucleation. For a significant particle production to take place, the model calculations of Korhonen et al. require a product of ammonia and
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hydrochloric acid partial vapour pressures of 100 ŽppbV. 2 at ambient temperatures between y2 and y48C. For this experiment Žq58C ambient temperatures., the measured ammonia concentrations would require hydrochloric acid concentrations above 300 ppb V to match the product of 100 ŽppbV. 2 . A further interesting point, however, is that just before the event of new particle formation, the total surface area dropped by ; 35% between 0400 and 0500 h due to the change to a less polluted air mass Žwhich was also the reason for the SO 2 to disappear.. As new particle formation and the condensation of precursors gases onto preexisting aerosol surface are two processes which compete for the consumption of the precursor reservoir, the decreasing aerosol surface area might have been one reason why nucleation was favoured during the ultrafine particle event. Marti et al. Ž1997. recently reported experimental evidence from the field for a anti-correlation between ultrafine concentrations and aerosol surface area. Though they observed H 2 SO4rH 2 O as dominating nucleating species, and nucleation at relative humidities much lower than in this experiment, such an argument should be able to be expanded to nucleation mechanisms involving other and more species.
7. Conclusions Experimental evidence for the processing of aerosol by an orographic cloud was gathered from a field experiment carried out in 1995 in Great Dun Fell, Northern England. During two periods, a shift in the aerosol size distribution was observed when comparing data from upwind and downwind stations. For two periods of 1 and 3 h, when the shift was pronounced, the mass increase due to cloud processing was estimated to be 1.2 mg my3 Ž"20%. and 1.7 mg my3 Ž"50%.. This amount makes up roughly a quarter of the preexisting submicron aerosol mass. As a major pathway for the production of particulate matter, liquid-phase oxidation of sulphur dioxide is proposed. Modelling results by Bradbury et al. Ž1999. strongly support such a reaction mechanism. Furthermore, large numbers of ultrafine particles were measured downwind of the mountain ridge with almost none present at the upwind sites. Although the various measured parameters of the field campaign are not sufficient to clarify the production process of this burst of ultrafine particles, some observations suggest that HCl gassed out when the cloud was evaporating. Another factor increasing the nucleation probability could have been the surface area which decreased by 35% prior to the ultrafine particle event. A statistical test yields the result that with a probability of 99%, the observed rates of ultrafine particles stand out of the dataset of the entire field campaign.
References Alkezweeny, A.J., 1995. Field observations of in-cloud nucleation and the modification of atmospheric aerosol size distributions after cloud evaporation. J. Appl. Meteorol. 34, 2649–2654. Bradbury, C., Bower, K.N., Choularton, T.W., Swietlicki, E., Birmili, W., Wiedensohler, A., Yuskiewicz, B.,
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Berner, A., Dusek, U., Dore, C.-J., McFayden, G.G., 1999. Modelling of aerosol modification resulting from passage through a hill cap cloud. Atmos. Res. 50, 185–204. Birmili, W., Stratmann, F., Wiedensohler, A., Covert, D., Russell, L.M., Berg, O., 1997. Determination of DMA transfer functions using identical instruments in series. Aerosol Sci. Technol. 27, 215–223. Bower, K.N., Choularton, T.W., Gallagher, M.W., Colville, R.N., Beswick, K.M., Inglis, D.W.F., Bradbury, C., Martinsson, B.G., Swietlicki, E., Berg, O.H., Cederfelt, S.-I., Frank, G., Zhou, J., Cape, J.N., Sutton, M.A., McFayden, G.G., Milford, C., Birmili, W., Yuskiewicz, B.A., Wiedensohler, A., Stratmann, F., Wendisch, M., Berner, A., Ctyroky, P., Galambos, Z., Mesfin, S.H., Dusek, U., Dore, C.J., Lee, D.S., Pepler, S.A., Bizjak, M., Divjak, B., 1999. The Great Dun Fell experiment 1995: an overview. Atmos. Res. 50, 151–184. Cape, J.N., McFayden, G.G., Storeton-West, R.L., Choularton, T.W., Gallagher, M.W., Bower, K.N., Lee, D.S., Dore, C.J., Berner, A., 1999. Field observation of SŽVI. oxidation in cloud. Atmos. Res. 50, 345–358. Chameides, W.L., Stelson, A.W., 1992. Aqueous-phase chemical processes in deliquescent sea-salt aerosols: a mechanism that couples the atmospheric cycles of S and sea salt. J. Geophys. Res. 97, 20565–20580. Easter, R.C., Peters, L.K., 1994. Binary homogeneous nucleation: temperature and relative humidity fluctuations, nonlinearity, and aspects of new particle formation in the atmosphere. J. Appl. Met. 33, 775–784. Girshick, S.L., Chiu, C.-P., McMurry, P.H., 1990. Kinetic nucleation theory: a new expression for the rate of homogeneous nucleation from an ideal supersaturated vapor. J. Chem. Phys. 93, 1273–1277. Hegg, D., 1985. The importance of liquid-phase oxidation of SO 2 in the troposphere. J. Geophys. Res. 90 ŽD2., 3773–3779. Hegg, D., 1989. The relative importance of major aqueous sulfate formation reactions in the atmosphere. Atmospheric Research 22, 323–333. Hoppel, W.A., Frick, G.M., Fitzgerald, J.W., Wattle, B.J., 1994. A cloud chamber study of the effect that non-precipitating clouds water clouds have on the aerosol size distribution. Aerosol Sci. Technol. 20, 1–30. Korhonen, P., Kulmala, M., Viisanen, Y., 1997. A theoretical study of binary homogeneous nucleation of water–ammonium chloride particles in the atmosphere. J. Aerosol Sci. 28, 901–917. Jaecker-Voirol, A., P. Mirabel, P., 1989. Heteromolecular nucleation in the sulphuric acid–water system. Atmos. Environ. 23, 2053–2057. Lelieveld, J., Heintzenberg, J., 1992. Sulfate cooling effect on climate through in-cloud oxidation of anthropogenic SO 2 . Science 258, 117–120. Marti, J.J., Weber, R.J., McMurry, P.H., Eisele, F.L., Tanner, D.J., Jefferson, A., 1997. Measurement of new particle formation and ultrafine particle growth rates at a clean continental site. J. Geophys. Res. 102 ŽD2., 4375–4385. Raes, F., Saltelli, A., Dingenen, V., 1992. Modelling formation and growth of H 2 SO4 –H 2 O aerosols: uncertainty analysis and experimental evaluation. J. Aerosol Sci. 23, 759–771. Saxena, V.K., 1996. Bursts of cloud condensation nuclei ŽCCN. by dissipating clouds at Palmer station, Antarctica. Geophys. Res. Lett. 23, 69–72. Schwartz, S.W., 1996. the whitehouse effect—shortwave radiative forcing of climate by anthropogenic aerosols Žan overview.. J. Aerosol Sci. 27, 359–382. ten Brink, H.M., Spoelstra, H., 1996. The interaction of sea-salt with nitric acid. Abstracts of the 1996 EAC, J. Aerosol Sci. 27, S667–S668, Suppl. 1. Tang, I.N., Munkelwitz, H.R., 1994. Water activities, densities, and refractive indeces of aqueous sulfates and sodium nitrate droplets of atmospheric importance. J. Geophys. Res. 99 ŽD9., 18801–18808. Warren, D.R., Seinfeld, J.H., 1985. Prediction of aerosol concentration resulting from a burst of nucleation. J. Colloid Interface Sci. 105, 136–142. Weber, R.J., McMurry, P.H., Eisele, F.L., Tanner, D.J., 1995. Measurement of expected nucleation precursor species and 3 to 500 nm diameter particles at Mauna Loa Observatory, Hawaii. J. Atmos. Sci. 52, 2242–2257. Wiedensohler, A., Hansson, H.-C., Orsini, D., Wendisch, M., Wagner, F., Bower, K.N., Choularton, T.W., Wells, M., Parkin, M., Acker, K., Wieprecht, W., Facchini, M.C., Lind, J.A., Fuzzi, S., Arends, B.G., Kulmala, M., 1997. Night-time formation and occurrence of new particles associated with orographic clouds. Atmos. Environ. 16, 2545–2560.
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Winklmayr, W., Reischl, G.P., Linde, A.O., Berner, A., 1991. A new electromobility spectrometer for the measurement of aerosol size distributions in the size range from 1 to 1000 nm. J. Aerosol Sci. 22, 289–296. Yuskiewicz, B.A., Stratmann, F., Birmili, W., Wiedensohler, A., Swietlicki, E., Berg, O., Zhou, J., 1999. The effects of in-cloud mass production on atmospheric light-scatter. Atmos. Res. 50, 265–288.
Climate-relevant modification of the aerosol size distribution by processes associated with orographic clouds W. Birmili b
a,)
, B. Yuskiewicz a , A. Wiedensohler a , F. Stratmann a , T.W. Choularton b, K.N. Bower b
a Institute for Tropospheric Research, Permoserstr. 15, D-04318 Leipzig, Germany UniÕersity of Manchester Institute of Science and Technology (UMIST), SackÕille Street, P.O. Box 88, Manchester M60 1QD, UK
Abstract Cloud processes can modify optical properties of aerosol particles. As aerosols have been recognized to play an important role in the earth’s radiation budget, the understanding of climate changes is also linked to cloud processes. During a field experiment at Great Dun Fell, Northern England in 1995, experimental evidence was found for the processing of aerosol by orographic clouds. During two periods ŽMarch 31, and April 3, 1995., a shift in the particle size distribution was detected when comparing data from upwind and downwind stations. For two periods of 1 and 3 h, when the shift was pronounced, the mass increase due to cloud processing was estimated to be 1.2 mg my3 Ž"20%. and 1.7 mg my3 Ž"50%.. This equals roughly a quarter of the pre-existing submicron aerosol mass. As a major source of particulate matter, liquid-phase oxidation of sulphur dioxide was identified. Modelling results from Bradbury et al. wBradbury, C., Bower, K.N., Choularton, T.W., Swietlicki, E., Birmili, W., Wiedensohler, A., Yuskiewicz, B., Berner, A., Dusek, U., Dore, C.-J., McFayden, G.G., 1999. Modelling of aerosol modification resulting from passage through a hill cap cloud.x strongly support such a reaction mechanism. Furthermore, large amounts of ultrafine particles were observed downwind the mountain ridge with almost none present at the upwind and summit sites. Some observations suggest that HCl may have degassed from the droplets when the cloud was evaporating. Another factor increasing the nucleation probability could have been the aerosol surface area which decreased by 35% prior to the occurrence of ultrafine particles. q 1999 Elsevier Science B.V. All rights reserved. Keywords: Cloud processes; Gas-to-particle conversion; New particle formation; Sulphate production; Cap cloud; DMPS
)
Corresponding author
0169-8095r99r$ - see front matter q 1999 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 9 - 8 0 9 5 Ž 9 8 . 0 0 1 0 6 - 9
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1. Introduction Aerosols are believed to play an important role for the earth’s radiation budget, and thus for climate. Two principal effects of this so-called whitehouse effect ŽSchwartz, 1996. have been recognized. The first is that airborne particles scatter part of the incident solar shortwave radiation back to space Ždirect effect of radiative forcing.. Particles of the Aitken and accumulation mode aerosol Ždry diameter: 0.05–1.0 mm., which represent the overwhelming fraction of particulate number concentration, scatter sunlight the more effectively the larger they are in optical diameter. This is important from the point of view that Aitken and accumulation mode particles are able to increase their size by in-cloud formation of sulphate during their activation as cloud condensation nuclei ŽLelieveld and Heintzenberg, 1992.. As a second effect, an increased aerosol particle number may raise the reflectivity of clouds Žindirect radiative forcing.. Ultrafine aerosol particles are produced by gas-to-particle conversion, and grow by coagulation and further condensation of condensable vapours Že.g., sulphuric acid, nitric acid, organic vapours, etc... This process may increase the number of Aitken and accumulation mode particles. If then a cloud is formed, more particles might be activated to cloud droplets. Consequently, the average cloud droplet size will be smaller compared to a situation involving lower particle numbers. With constant liquid water content, the cloud albedo may be increased due to a higher optical activity of smaller cloud droplets. Both the indirect and the direct radiative forcing lead to a net cooling of the earth’s surface, and thus are able to partially offset the greenhouse effect. This study investigates two climate-relevant effects that cloud processes might induce. Ž1. Increase of aerosol particles in size after their passage through a cloud due to aqueous phase chemical reactions in cloud droplets. Several works ŽHegg, 1985; Chameides and Stelson, 1992. report that the in-cloud oxidation of sulphur in the atmosphere constitutes a major pathway for transferring mass from the gas phase to the particulate phase. This has also been demonstrated recently by cloud chamber experiments ŽHoppel et al., 1994.. The basic mechanism is that cloud droplets take up soluble sulphur dioxide ŽSO 2 . which is then oxidised in the liquid phase to sulphate ŽSO42y . under the consumption of either H 2 O 2 or O 3 ŽHegg, 1989.. In acidic droplets Ž- pH 6., H 2 O 2 is recognized as the major oxidant, whereas above pH 6, ozone becomes more relevant. For the latter oxidation process, the presence of ammonia is required. As a result of the additional ionic matter formed in the liquid phase, the particle may be larger in diameter after the cloud passage. As a consequence, the optical properties of the particles change along with the change in size. Especially Aitken and accumulation mode particles become optically more efficient as they grow, and thus, effect visibility and radiative forcing. The latter aspect is expanded in a separate paper ŽYuskiewicz et al., 1999. based on the measurements of this paper. Only few field experiments have been reported which quantified a change in the size distribution due to cloud processing. Alkezweeny Ž1995. report indications of particle growth after an air parcel had passed through a summer cumulus cloud.
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Ž2. Production of new ultrafine aerosol in association with clouds. On the one hand, aerosol particles are removed from the atmosphere by processes like in-cloud scavenging, below-cloud scavenging, and dry deposition; on the other hand, the atmospheric aerosol budget is being supplied with new particles by direct particulate emission, and by homogeneous nucleation of new particles from the gas phase, the latter of which contributes especially to produce new relevant numbers of new particles. Fresh aerosol particles with diameters smaller than 10 nm may nucleate if gaseous precursor species are available locally in the atmosphere at supersaturation. The most important of these species has been recognized to be sulphuric acid ŽH 2 SO4 . together with water vapour. Sulphuric acid is formed in the atmosphere by gas-phase oxidation of sulphur dioxide ŽSO 2 . in the presence of hydroxyl ŽOH. radicals ŽRaes et al., 1992; Easter and Peters, 1994.. The nucleation process depends strongly on factors such as temperature, partial pressure of condensable material and the surface area of pre-existing particles ŽWarren and Seinfeld, 1985; Jaecker-Voirol and Mirabel, 1989.. Existing nucleation theories, however, predict nucleation rates that differ by orders of magnitudes ŽGirshick et al., 1990.. Nucleation rates observed in the atmosphere differ from theoretically predicted values by similar amounts ŽWeber et al., 1995.. One reason might be that fundamental thermodynamic parameters Že.g., vapour pressures. are not known with suitable accuracy. Another is that in the atmosphere, additional species are likely to be involved in nucleation processes Že.g., NH 3 , HCl, HNO 3 .. A number of field experiments report observations of ultrafine particles in the outflow of clouds ŽHoppel et al., 1994; Wiedensohler et al., 1997.. Saxena Ž1996. found increased aerosol number concentrations just after clouds had been dissipating at Palmer Station, Antarctica—an observation which could have been caused by new particle formation.
2. Field experiment A field experiment was carried out in Great Dun Fell ŽNorthern England. in spring 1995, where an orographic cloud was formed on a mountain ridge. This cloud reactor served to investigate the influence of a cloud on the aerosol size distribution with emphasis being directed towards detecting small changes during the passage. Four Differential Mobility Particle Sizers ŽDMPS. were operated at the sites of Fell Gate Župwind., Mine Road Župwind, near cloud base., Summit, and Moor House Ždownwind.. Other physical, chemical and meteorological measurements provided an extensive dataset, which yield to a better understanding of cloud processes and their implications. The lead article of this field experiment ŽBower et al., 1999. gives an overview of the Great Dun Fell experiment 1995 and its basic results.
3. Instrumental Four Differential Mobility Particle Sizers ŽDMPS. were used to determine particle size distributions. Each system consists of two Hauke-type Differential Mobility Analy-
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sers ŽDMAs. —therefore called a Twin DMPS system. A DMA basically segregates aerosol particles according to their electrical mobility which is transferred to a size distribution after. Technically, the DMAs follow the design of Winklmayr et al. Ž1991. ŽDMA type 3r150. with variations in the exact dimensions. In particular, two DMAs with different center rod lengths were used to measure different particle size ranges Žcf. Table 1 for technical specifications and flow rates of the DMAs.. These are denoted as ‘UDMA’ Žshort centre rod., and as ‘DMA’ Žlong centre rod. in the following. A Condensation Particle Counter CPC Žmodel 3010; TSI, St. Paul, MN. counted aerosol particles downstream of the DMA, whereas a UCPC Žmodel 3025, TSI. counted for the UDMA. At all measurement sites, impactors Žcut-off size: 3 mm at ambient conditions. were mounted on masts Žheight: 4 m. and provided interstitial aerosol samples. To insure that the particle size measured refers to the dry size of the particles, the sheath air supplying the DMAs was dried at ambient temperature before entering the laboratory caravans. At the stations Fell Gate, Summit, and Moor House, the full Twin DMPS setup ŽDMA q UDMA. was operating. At Mine Road, only one medium DMA Ž31 diameter channels in the range 22–676 nm. was used in conjunction with a UCPC 3025 because no UDMA was available for that site. All DMAs were operated in a channel-wise stepping mode. The diameter channels were evenly spaced on a logarithmic scale Ž18 channels 3.1–25 nm for the UDMA, 30 channels 25–794 nm for the DMA.. The sampling time was 15 min for an entire scan. All DMA flow rates were set by adjustable critical orifices Žneedle valves. using a bubble flow meter ŽGilibrator-2 Calibration System, Senseydyne, Clearwater, FL, USA.. 3.1. Error estimation for the DMPS technique The experimental errors connected with the measurement technique were estimated as best as possible. The following errors were quantified and accounted for in the evaluation of the final size distributions. The finite number of particles counted in each measurement bin causes a statistical error ŽPoisson error.. This is relevant in the size range 3–25 nm measured by the UDMA. The main reasons for low count numbers are the low effective sampling flow of the UCPC 3025 Ž0.03 lpm., losses of ultrafine particles due to Brownian diffusion, and the low charging efficiency of ultrafine particles. To compensate this effect at least partially, a sampling time of 45 s was selected for each diameter channel that is - 25 nm.
Table 1 Electrode length and air flow specifications for the DMAs used for this work DMA type
Center rod length Žcm.
Sheath air flow Žlpm.
Aerosol flow Žlpm.
Measured particle size range Žnm.
UDMA-Hauke short DMA-Hauke medium
11.0 28.0
20.0 5.0
2.0 0.5
3–25 25–794
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Another source of instrumental error is the use of adjustable critical orifices Žneedle valves. to regulate the DMA flow rates. The variations of the flows through such variable orifices were empirically determined to "0.7% during the field experiment. As the sheath air to aerosol flow ratio is 10:1, and two separate orifices Žsheath air q excess air. are involved, this relatively small error may sum up to "10% regarding the aerosol sample flow. Considering simple DMA transfer theory, this may falsify the concentrations measured by similar amounts. Therefore, we included the "10% error in all error bars. Important for the evaluation of the size distribution is also the knowledge of the transfer function of the DMAs, especially of the UDMA ŽBirmili et al., 1997.. As a result of particle losses due to particle diffusion in the devices, the transmission of ultrafine particles decreases strongly for small sizes Ž Dp - 10 nm for the UDMA.. Other systematic errors Žparticle losses due to diffusion in inlets, connecting tubings, charge neutralizers. are estimated to be below 5%. Another error, though difficult to estimate, occurs when the air mass sampled by the system changes a lot while the DMPS is scanning. Such data points were removed from the data set. An additional error may occur if the sheath air in a DMA is not completely dry, which can result in an overestimation of the dry particle size. This aspect is addressed later in the paper.
4. Flow connectivity The four measuring sites ŽFell Gate, Mine Road, Summit, and Moor House. are aligned along the expected flow path, however, not on an exact straight line. The distances are 1.8 km between Fell Gate and Mine Road, 1.2 km between Mine Road and Summit, and 4.7 km between Summit and Moor House. For more details of the terrain, see Bower et al. Ž1999.. For the purpose of comparing measurements between different sites, evidence must be given that the air flows continuously across the mountain ridge, and the different sites are ‘connected’. One cannot strictly prove that the same air mass was sampled at all measurement sites Žlike in an ideal Lagrangian experiment.. One can, however, assure by a number of means Žshown below. that similar streamlines of the airflow were sampled. This can be done under the assumption that the aerosol to be observed is horizontally homogeneous within a range of 1–3 km.
Table 2 Run periods for which flow connectivity was established Run period of connected flow
Fell Gate upwind Ž435 m a.s.l..
Mine Road upwind Ž680 m a.s.l..
Summit Ž845 m a.s.l..
Moor House downwind Ž560 m a.s.l..
I II III
cloud-free cloud-free cloud-free
cloud-free partly in cloud partly in cloud
cloud-free partly in cloud always in cloud
cloud-free cloud-free cloud-free
April 1, 1200–1800 h March 31, 1200–1800 h April 3, 0000–1800 h
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To establish flow connectivity, we used various data from all sites: particle size distributions, wind speed, wind direction, temperature profiles, liquid water content wmeasured by a particle volume monitor ŽPVM.x, cation concentrations of Naq, Kq, Mg 2q, and Ca2q ŽRotheroe–Mitchell impactor data, see Dore et al., 1999., and profiles of NO x Žsee Cape et al., 1999.. For the purpose of this work, three periods with evidence for flow connection were investigated Žcf. Table 2.: one event featuring cloud-free conditions, and two events with a cloud present on the mountain ridge. 4.1. Run period I (cloud-free conditions) Fig. 1 shows a measurement from April 1, 1995, 1600 h ŽMoor House 15 min later due to the travelling time of the air mass. illustrating the quality of the DMPS measuring technique. The size distributions of all stations agree very well within the instrumental error range in a wide size range Ž5–794 nm.. At the time, no cloud was on top of the ridge Žzero liquid water content at all stations.. This agreement indicates that the same air was investigated. Divergences occur only in the ultrafine range for Dp - 5 nm. Error bars, as described in the preceding text, illustrate the measurement uncertainty. To make the plot not too busy, error bars were displayed for one station only. It can be seen that for 10 - Dp - 400 nm, the overall error is fairly constant Ž"10%., mainly due to flow rate variations caused by adjustable orifices. Near the upper end of the distribution Ž Dp ) 400 nm., the statistical error increases slightly when concentrations fall short of 100 cmy3 Žd Nrdlog Dp .. Similarly, error bars increase for Dp - 10 nm due to the degrading counting statistics Žlow sampling flow of the UCPC..
Fig. 1. Dry particle size distributions during run period I.
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Meteorological observations taken from this period strongly support flow connection. The wind speed was fairly high at all sites Ž; 15 m sy1 on Summit. with wind directions at all sites being perpendicular to the ridge, and rather similar ŽFell Gate and Mine Road: ; 3008, Summit: ; 2508, Moor House: ; 2708.. Such conditions provide a steady airflow across the ridge. Dry ambient temperatures were: Fell Gate 108C Ž435 m., Moor House 9.28C Ždownwind, 560 m., Mine Road 8.28C Ž680 m., and Summit 6.08C Ž845 m.. This is consistent with the assumption that an air mass is lifted adiabatically when passing over the ridge. Following such a model, Fell Gate is ideally 4.0 K, Mine Road 1.6 K, and Moor House 2.8 K warmer than Summit. 4.2. Run period II (cloud) Fig. 2 shows the particle size distributions of all stations on March 31, 1645 h ŽMoor House 1700 h.. A good agreement in the size range 20–80 nm can be seen. In that size range, we expect no significant change of the size distribution during a cloud passage. One reason is that particles 20–80 nm are too large to coagulate efficiently with cloud droplets. They are also too small to be activated as cloud droplets. Note that a large fraction of the accumulation and Aitken mode aerosol with Dp ) 80 nm are absent at the Summit site due to in-cloud scavenging Žliquid water content ; 0.6 g cmy3 .. Also in this case, the meteorological data support the flow to be connected across the ridge. Southwesterly winds Žspeed ) 5 m sy1 . prevail at all stations Ždirections ; 2408–3108.. The temperature profiles stay well-separated with the gaps between the profiles being smaller than those derived from the adiabatic lift of an air parcel. This can be explained
Fig. 2. Dry particle size distributions during run period II.
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Table 3 Activated particle volume fractions during run periods II and III Run period
Time span
Activated particle volume fraction Ž Dp -800 nm.
Liquid water content at the Summit station Žg cmy3 .
II (March 31, 1995)
1200–1330 h 1345–1415 h 1430–1800 h
96.0"0.9% no activation 86.0"4.3%
0.2 0.0–0.1 0.0–0.8
III (April 3, 1995)
0000–1400 hr entire period
95.4"1.9%
0.2–0.5
by a nonzero liquid water content on the pathway between the stations. Some measured species Že.g., NO x , cations. are expected to be conserved during a cloud passage, and can thus be used as a tracer. An analysis of the NO x profiles ŽCape et al., 1999. shows a good correlation between all stations for period II. After subtracting an instrumental offset from the Moor House data, a linear correlation coefficient of 0.90 was determined between the NO x time histories from Fell Gate and Moor House. To obtain information about the activation of particles in the cloud, the number size distributions were transferred to volume size distributions. From these, the activated particle volume fraction was calculated from Summit Žin-cloud. and Fell Gate Žout-ofcloud. data. The results are displayed in Table 3.
Fig. 3. Dry particle size distributions during run period III.
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4.3. Run period III (cloud) Fig. 3 shows an exemplary measurement taken at 0515 h on April 3, 1995 ŽMoor House 0530 h.. We see once again a good agreement of the DMPS spectra in the size ranges where we expect it. Part of the accumulation and Aitken mode particles with Dp ) 60 nm, however, are scavenged at the Summit site Žliquid water content ; 0.2 g cmy3 .. As for run period II, the activated particle volume fractions were calculated ŽTable 3.. Another feature of the size distributions is the occurrence of large concentrations of ultrafine particles at Moor House. This feature will be discussed separately below. Also in this case, the meteorological data support strongly the assumption of connected flow during the period of concern. The wind speed at all stations remains quite stable ŽFell Gate ; 4 m sy1 the lowest, Summit ; 15 m sy1 the highest. with all stations agreeing reasonably well in a westerly wind direction. The temperature profiles remain well-separated with their differences being similar to period II. The Rotheroe– Mitchell impactor data Žcation mass concentrations. of Fell Gate and Moor House agree reasonably well indicating that the same air mass is investigated. Moreover, the NO x profiles from Fell Gate, Summit and Moor House are similar. To sum up, a large number of observations indicate that the airflow was connected during periods I–III.
5. Sulphate production in the liquid phase During periods when the airflow was connected, the size distributions of different stations were carefully compared. Size distributions as in Fig. 2 were found, when the DMPS spectrum of Moor House revealed a significant shift towards larger particle sizes in the Aitken and accumulation mode range Ž60–400 nm.. Eight such distributions were found during period II and nine during period III, respectively. A possible explanation could be the in-cloud oxidation of soluble gases as described in the introduction. Two cases, when this effect became quite obvious, will be discussed, and the effect will be quantified. To illustrate the shift in particle size distribution, the measurement points 1615, 1630, and 1645 h from March 31 Žperiod II. were averaged ŽFig. 4.. The Mine Road data is not displayed in the figure because the station changed from in-cloud to out-of-cloud several times during the period of concern. A suitable particle size interval for a quantification of the growth effect is 60–400 nm, since this is the range in which we observe significant changes in the size distribution, and the range in which error bars are small. For the interval 60–400 nm, the total particle concentration and the particle volume concentration were calculated. To avoid particle volume concentrations to be influenced by the total particle number concentration Žwithin the error range of the instruments., the particle number size distributions were normalised to the total number concentrations of Fell Gate. Thus, we make provision that only the net effect Žshift in size distribution. accounts for differences in the particle volume concentrations on both sides of the mountain ridge.
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Fig. 4. Shift in the particle size distribution between upwind and downwind station during run period II Ž1615–1645 h..
5.1. Cloud-free conditionsr run period I (April 1) No effect: during this period, little variation can be seen between the different profiles of particle volume concentration Žcf. Fig. 5.. 5.2. Shift in size distributionr run period II (March 31) During period II, particle volume concentrations from different stations agree well between 1200 and 1500 h Žcf. Fig. 6.. Afterwards, as Summit goes into cloud Žnonzero
Fig. 5. Comparison of particle volume concentrations Ž60 nm - Dp - 400 nm. at different sites for cloud-free conditions Žperiod I..
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Fig. 6. Comparison of particle volume concentrations Ž60 nm - Dp - 400 nm. at different sites for a cloud event Žperiod II.. Comparison to time histories of liquid water content and sulphur dioxide.
liquid water content., the curve of Moor House drifts upward slightly being significantly larger than Fell Gate and Mine Road between 1600 and 1700 h. Note that the curve of Mine Road drops after 1615 h because the station enters into the cloud at that time Žalso indicated by a nonzero liquid water content. with a considerable fraction of the particle volume being scavenged. Such a difference between particulate volumes on both sides of the hill regarding sulphate production is supported by Cape et al. Ž1999. who observed that droplets of the cloud took up a significant portion of SŽVI.. The excess volume at Moor House after 1600 h coincides with a slightly increasing input concentrations of SO 2 after 1600 h, as can be seen in the bottom diagram of Fig. 6. In contrast to the period 1600–1700 h, however, we see no indications of particle growth between 1200 and 1400 h. During that period, SO 2 was even higher, at a similar liquid water content of ; 0.2 g cmy3 . The levels of gaseous H 2 O 2 can neither explain the difference between both episodes, since the levels were equally low, around 0.1 ppb in both cases. By comparing the particle volume concentrations, an average difference of 0.69 mm3 cmy3 Ž"20%. could be determined using data from 1600–1645 h Žsee also Table 4.. This corresponds to an increase of the aerosol mass concentration by 1.21 mg my3 Ž"20%. assuming that the additional mass consists mainly of ammonium sulphate Ždensity 1.76.. The effect cannot be considered negligible since, if the theory of sulphate
252
Run period
Time span
Measured volume shift Žmm3 cmy3 .
Corresponding mass shift Žmg my3 . a
II (March 31, 1995)
1200–1800 hr entire period 1600–1645 hr intense production
0.29
0.51
0.69
1.21
0000–1400 hr entire period 0100–0245 hr intense production
0.56
0.98
0.98 b
1.72 b
III (April 3, 1995)
a
Percentage volume increase in interval Ž0.06–0.8 mm.
Mixing ratio of SO 2 Žppb V.
Liquid water content at the Summit station Žg cmy3 .
23%
0.2–0.3
0.4–0.5
25%
0.1–0.3
0.3–0.4
Assuming the density 1.76 of ammonium sulphate. Cannot be explained entirely by liquid-phase oxidation of sulphur dioxide. See details in the text.
b
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Table 4 Calculated volume and mass shifts of the particulate aeosol during a cloud passage for two selected run periods ŽII, III.
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production holds, roughly a quarter of the particle volume Ž60–400 nm. was produced in the cloud. 5.3. Shift in size distributionr run period III On April 3, 1995, when a thick cloud enveloped the mountain ridge, we also observed a systematic shift of the particle size distribution to larger sizes in the Aitken and Accumulation mode range, similar to that of period II described above. Looking at the time histories of particle volume concentrations Žcf. Fig. 7., it seems that some continuous particle growth happened through the whole time period 0000–1400 h, although it was not very pronounced except during the episode 0100–0400 h, when the shift could be seen clearly in the size distributions. This period of a strong shift coincides with the beginning of an episode with elevated SO 2 concentrations Žcf. bottom diagram of Fig. 7. supporting the theory of particle growth by sulphate production. After 0230 h, the production rate shrinks. As one possible reason, we suspect the decreasing droplet volume available for liquid-phase reactions that results from a drop in liquid water content Žcf. diagram in the middle of Fig. 7.. During the phase of intense
Fig. 7. Comparison of particle volume concentrations Ž60 nm - Dp - 400 nm. at different sites for a cloud event Žperiod III.. Comparison to time histories of liquid water content and sulphur dioxide.
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production 0100–0245 h, the average additional volume downwind the cloud was 0.98 mm3 cmy3 corresponding to a mass shift of 1.72 mg my3 . Averages for the entire period 0000–1400 h are lower, 0.56 mm3 cmy3 and 0.98 mg my3 Žall values " 20%., respectively. Evidence for sulphate production was gathered from modelling of in-cloud sulphate production in association with orographic clouds. Details of the model and the full results are presented in Bradbury et al. Ž1999.. As an input, the model uses measured particle size distributions from Fell Gate and calculates distributions at Moor House, modified by the cloud process. Bradbury et al. found that the cloud model reproduces the trend of the real size distribution measurements at Moor House reasonably well. It must be stated, however, that the observed maximum mass shift of 1.72 mg my3 in period III cannot entirely be explained by the liquid-phase oxidation of SO 2 . The formation of a corresponding amount of ammonium sulphate would require more SO 2 Ž; 0.7 ppb V. than was actually available in the air mass upwind the cloud Ž0.2–0.4 ppb V.. Besides, no SO 2 measurements were made at Moor House, and hence, no statement can be given about SO 2 consumption during the cloud process. Besides the conversion of matter other than SO 2 to the solid phase, another effect could be responsible for the divergence between the mass shift and the observed SO 2 concentrations. This is an eventual overestimation of the dry particle size in the DMAs. Tang and Munkelwitz Ž1994. report a hysteretical behaviour, when particles are humidified to high relative humidities, and are subsequently dried. Dry ammonium bisulfate particles, as a realistic example, convert rapidly to liquid particles Ždeliquescence., and grow further, when 80% relative humidity is exceeded. After that, however, they do not reach their initial dry size unless dried to a relative humidity below 37%. In the field experiment, the first mentioned process would correspond to the humidification of the particles, as relative humidity increases, while the air parcel is ascending. Eventually, the relative humidity was below the deliquescence point of the particles at the upwind measurement station ŽFell Gate.. The second Ždrying. process takes place inside the DMAs. There, the authors assume relative humidities lower than 25%, since the sheath air was conditioned by adsorptional dryers before entering the DMAs. If the wet particles, however, need a noticeable time Ža few milliseconds. to get in equilibrium with the dry air, they will shrink to their final dry size only during the passage through the DMA, and, consequently, their dry size will be overestimated. An overestimation of the dry particle size at the downwind station ŽMoor House. of, e.g., 5% would lead to an overestimation of particle volume Žand mass. by 15%; it can be seen that the calculated mass shifts are quite sensitive to this effect. This could therefore explain the overestimation of the maximum mass shift of 1.72 mg my3 between 0100–0245 h in period III. For the discussed reasons, the value 1.72 mg my3 is assigned with an uncertainty of "50% in the conclusions of this paper.
6. Formation of ultrafine particles Special attention was also paid to the occurrence of ultrafine particles. The performance of three DMPS systems with a lower detection limit of Dp ; 3 nm ŽFell Gate,
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Summit, and Moor House. permits an intercomparison of ultrafine concentrations of the same air mass, once flow connectivity is established. During the entire measurement campaign, ultrafine particles Ž Dp - 20 nm. were observed most of the time, and frequently, in the shape of a mode. Concentrations in that size range were similar at all stations Fell Gate, Summit, and Moor House Žat Mine Road, no ultrafine particle sizer was operated.. Significant differences between different sites occurred only in the size fraction 3–8 nm. This is different from observations by Wiedensohler et al. Ž1997. who report, from a previous field experiment at the same location two years earlier, a new ultrafine mode with mode diameters of 5–15 nm in the outflow of the cloud. Fig. 8 compares upwind ŽFell Gate. and downwind ŽMoor House. concentrations of ultrafine particles Ž3–8 nm. for five periods ŽI, II, IIIa–c.. Note that period III was divided into three parts to point out the period IIIb Ž0500–0800 h. during which we report the highest concentrations of ultrafine particles at Moor House. Data from the Summit station are not displayed, since they follow closely those from Fell Gate. The integral number concentration of ultrafine particles was calculated by numerically integrating the size distributions up to Dp s 8 nm. For the noncloud period I, the concentrations on both sides of the hill nearly show a 1:1 correspondence, with a little excess at Moor House. This also holds for the cloud event II. During cloud event III, however, ultrafine concentrations at Moor House exceeded those at Fell Gate substantially between 0500–0800 h. 6.1. ObserÕations during run period III On April 3, westerly winds carried Atlantic air across Great Dun Fell. As deduced in the preceding text, the flow was connected between 0000 and 1400 h. Fig. 9 shows time
Fig. 8. Comparison of ultrafine particle concentrations Ž3–8 nm. of Fell Gate and Moor House.
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Fig. 9. Ultrafine particle concentrations, liquid water content, and sulphur dioxide during run period III featuring large concentrations of ultrafine particles at Moor House.
histories of the ultrafine concentrations at Fell Gate, and Moor House Žtop diagram. plus liquid water content Ždiagram in the middle. and sulphur dioxide Žbottom diagram..
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Aerosol surface concentration was determined from DMPS size distributions by numerical integration assuming spherical particles and is plotted in Fig. 10 Ždiagram in the
Fig. 10. Aerosol surface concentrations, temperatures, and nitrate mass concentrations during run period III.
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middle.. At the beginning and at the end of the run, ultrafine concentrations stayed below 1000 cmy3 at both stations. Between 0500 and 0800 h Žperiod IIIb., however, ultrafine concentrations downwind ŽMoor House. exceeded those at Fell Gate by factors up to 20. Ultrafine concentrations Ž3–8 nm. reached 5000 cmy3 at Moor House, whereas in the complementary size interval 8–800 nm, only ; 2000 cmy3 were found. The overwhelming number of atmospheric particles was thus within the ultrafine range. 6.2. Statistical assessment of the data points of sub-period IIIb The aim of this section is to judge whether the observed event of new particle formation stands out statistically in comparison to the rest of the periods of the field campaign. The methods we employed follow standard procedures used in statistical textbooks. As mentioned, we discern five sample periods ŽI, II, IIIa–c; cf. Table 5.. As a convenient variable to characterize excess of ultrafine particles at Moor House, we used a relative difference X of ultrafine particles between Moor House and Fell Gate defined as X s Ž NM H y NF G .rŽ NM H q NF G .. NM H and NF G are ultrafine particle concentrations Ž3–8 nm. at the two stations. The higher the value of X, the larger is the excess of ultrafine concentrations downwind. A negative X indicates higher ultrafine concentrations at Fell Gate. To account for error bars as realistically as possible, the individual error s i of each measurement point Ni was calculated from the absolute number of particles that were actually counted in the size interval 3–8 nm ŽPoisson error. plus the 10% uncertainty of the DMPS measurement. The measurement points were averaged for each of the sample periods. When calculating the sample standard deviation s X of each sample period, we considered the individual error s i as well as the deviation of each measurement point Ni
Table 5 Tests of hypotheses and significance for the occurrence of excess ultrafine particles at Moor House Sample period, time
n
X
sX
sx
Z
H0
Accept H 0?
II I IIIa IIIb IIIc
22 22 20 12 20
y0.07 0.13 0.47 0.64 0.18
0.50 0.47 0.81 0.52 0.66
0.108 0.103 0.185 0.156 0.150
y0.67 1.32 2.54 4.12 1.21
mX s 0 mX s 0 mX s 0 mX s 0 mX s 0
yes yes yes no yes
XI y XA
S X IyXA
Z
0.21 y0.33 y0.51 y0.05
0.149 0.211 0.187 0.182
1.39 y1.58 y2.72 y0.25
mI s mA mI s mA mI s mA mI s mA
yes yes no yes
April 1, 12:00–17:30 March 31, 12:00–17:45 April 3, 00:00–04:45 April 3, 05:00–08:00 April 3, 08:25–13:45
Comparison of sample periods Žperiod I vs. period A g II, IIIa–c. I Žcloud-free. vs. II I Žcloud-free. vs. IIIa I Žcloud-free. vs. IIIb I Žcloud-free. vs. IIIc
X
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from the sample mean X. To give more weight to measurement points with a small standard deviation s i , the mean values X were calculated using the inverse square root of s i as a convenient weight for each Ni . In Table 5, it can be seen that X assumes its largest values during periods IIIa and IIIb when we found the most excess of ultrafine particles downwind the cloud. In a first step, we tested whether data from any of the sample periods ŽI, II, IIIa–c. deviate from X s 0 at all. Therefore, a zero hypothesis H 0 : m X s 0 was proposed for the population of each sample period. The standardised mean Z s XrŽ s Xr6n y 1. was calculated for each sample period. For a significance level a s 0.01, H 0 is acceptable if y2.58 - Z - q2.58 Žtwo-tailed test.. In this context, 1 y a s 99% can be regarded as the probability that our zero hypothesis is true if Z is within the range as indicated below. As we can see from Table 5, the variable X deviates significantly from zero only for the sample period IIIb, since H 0 was rejected in this case, while it was accepted in all other cases. At an alternative level a s 0.05, H 0 would have been rejected for one more period: IIIa. Our next Žmore important. step is to investigate whether any of the periods II and IIIa–c Žthe case of a cloud. can be distinguished statistically from our reference sample, the cloud-free case I, where we expect no change of the ultrafine particle number across the hill. Hereto, the differences between the variables X I Žperiod I. and XA Žperiod A g II, IIa–c. and their corresponding standardised means ZX were calculated Žfour bottom rows of Table 5.. The new zero hypothesis was that the means of the two periods agree Ž m I s m A . leading to similar results: again for period IIIb, H 0 was rejected, while it was acceptable for all other cases. This means that within a probability of 99%, the samples taken during period IIIb were different from those during the cloud-free period I and can be considered a unique part of the dataset. 6.3. Exclusion of entrainment; discussion A detailed meteorological analysis yields no signs of entrainment of air into the cap cloud, suggesting that ultrafine particles were produced in the airflow downwind. If there was entrainment of dry air from aloft ŽKelvin–Helmholtz instabilities., the liquid water content on Summit should be lower than suggested by an adiabatic lift model. Such a model estimates the increase of liquid water content ŽLWC. with height to 0.10 g cmy3 per 50 m ascent. Fig. 9 Žmiddle. shows an LWC of 0.15 g cmy3 at Mine Road Ž680 m., and 0.5 g cmy3 at Summit Ž845 m. which matches the calculated LWC difference of 0.33 g cmy3 . This is the case between 0100–0300 h, and 0900–1030 h. Between these times Žwhen ultrafine particles were observed., this calculation cannot be carried out, since Mine Road was out of cloud Žzero LWC.. The temperature difference between both stations, however, remains fairly constant through the run indicating that no much atmospheric change happened between Mine Road and Summit. The cloud base most likely stayed just above Mine Road during the time when ultrafine particles were observed. This is also indicated by the small spikes in the LWC profile of Mine Road when the cloud base touches the station. It is thus probable that the observed large concentrations of ultrafine particles were produced in the air flow downwind. A further
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argument for particle nucleation shortly before the measurement on April 3, 1995 is the fact that the particles appear only in the size range between 3 and 8 nm, near the lower detection limit of the system. The concentration of SO 2 , the most important precursor for H 2 SO4 , had its maximum a few hours before the ultrafine particle event, between 0200–0400 h. During the actual event Ž0500–0800 h., the SO 2 level was comparably low, near 0.1 ppb V. Moreover, at that early time of day Žsunrise 0530 h., there was no or only very little incident solar radiation that could have generated a significant amount of hydroxyl ŽOH. radicals, which is the preferred oxidant for SO 2 . These facts suggest that also nucleation mechanisms other than binary H 2 SO4rH 2 O nucleation were relevant for the formation of the observed ultrafine particles. An alternative that merits a discussion in the context of this field experiment is the formation of ammonium chloride particles, which was theoretically investigated by Korhonen et al. Ž1997.. The latter authors say, on the basis of model calculations, that it is highly improbable for ammonia and hydrochloric acid to nucleate under dry atmospheric conditions. If, however, high relative humidities and low temperatures are attained like in the case of an evaporating cloud, such nucleation is considered possible to take place in the atmosphere. This is the result of an improved nucleation rate calculation, which takes hydrate interactions into account. Ammonia, the first precursor of ammonium chloride aerosol, was measured at Moor House with an AMANDA system Žconductivity measurement.; ammonia concentrations were constantly low, but nonzero Ž; 0.3 mg my3 . between April 2, 2200 h, and April 3, 1000 h, which includes the nucleation event, and the preceding 7–8 h. The second reaction partner, hydrochloric acid was not measured directly in this field experiment. From laboratory experiments, however, it is known that hydrochloric acid can gas-out from liquid droplets under conditions like in a dissipating cloud Žten Brink and Spoelstra, 1996.. Assuming that both HCl and HNO 3 are resolved in a cloud droplet, nitrate tends to remain with the droplets, while gaseous hydrochloric acid is expelled, when the droplet size decreases during cloud evaporation. This reaction requires a significant fraction of the aerosol to consist of sea-salt, which is likely to be the case for the investigated air mass, originating from the Atlantic. Additional support for the theory of outgassing HCl results from the trend of ionic nitrate mass concentrations measured during the experiment by Berner impactors Žcf. the overview paper by Bower et al., 1999.. Deviations between the stations of Fell Gate and Moor House occurred only in the largest impactor stage Ž1.6–5.1 mm aerodynamic diameter. which accumulates roughly 75% of the particulate mass for Dp - 5.1 mm. It was observed that, along with a change in air mass after 0400 h, the nitrate concentrations at Moor House exceeded those at Fell Gate after 0600 h though before, the reverse was the case. This could be interpreted as an enhanced attachment of nitrate to the largest aerosol particles as a result of the above reaction Ždisplacement of HCl; residence of nitrate. during the cloud passage. Using the suggestions of Korhonen et al. Ž1997., however, the occurrence of ultrafine particles in this experiment can, however, still not be satisfactorily explained by the ammonia and hydrochloric acid nucleation. For a significant particle production to take place, the model calculations of Korhonen et al. require a product of ammonia and
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hydrochloric acid partial vapour pressures of 100 ŽppbV. 2 at ambient temperatures between y2 and y48C. For this experiment Žq58C ambient temperatures., the measured ammonia concentrations would require hydrochloric acid concentrations above 300 ppb V to match the product of 100 ŽppbV. 2 . A further interesting point, however, is that just before the event of new particle formation, the total surface area dropped by ; 35% between 0400 and 0500 h due to the change to a less polluted air mass Žwhich was also the reason for the SO 2 to disappear.. As new particle formation and the condensation of precursors gases onto preexisting aerosol surface are two processes which compete for the consumption of the precursor reservoir, the decreasing aerosol surface area might have been one reason why nucleation was favoured during the ultrafine particle event. Marti et al. Ž1997. recently reported experimental evidence from the field for a anti-correlation between ultrafine concentrations and aerosol surface area. Though they observed H 2 SO4rH 2 O as dominating nucleating species, and nucleation at relative humidities much lower than in this experiment, such an argument should be able to be expanded to nucleation mechanisms involving other and more species.
7. Conclusions Experimental evidence for the processing of aerosol by an orographic cloud was gathered from a field experiment carried out in 1995 in Great Dun Fell, Northern England. During two periods, a shift in the aerosol size distribution was observed when comparing data from upwind and downwind stations. For two periods of 1 and 3 h, when the shift was pronounced, the mass increase due to cloud processing was estimated to be 1.2 mg my3 Ž"20%. and 1.7 mg my3 Ž"50%.. This amount makes up roughly a quarter of the preexisting submicron aerosol mass. As a major pathway for the production of particulate matter, liquid-phase oxidation of sulphur dioxide is proposed. Modelling results by Bradbury et al. Ž1999. strongly support such a reaction mechanism. Furthermore, large numbers of ultrafine particles were measured downwind of the mountain ridge with almost none present at the upwind sites. Although the various measured parameters of the field campaign are not sufficient to clarify the production process of this burst of ultrafine particles, some observations suggest that HCl gassed out when the cloud was evaporating. Another factor increasing the nucleation probability could have been the surface area which decreased by 35% prior to the ultrafine particle event. A statistical test yields the result that with a probability of 99%, the observed rates of ultrafine particles stand out of the dataset of the entire field campaign.
References Alkezweeny, A.J., 1995. Field observations of in-cloud nucleation and the modification of atmospheric aerosol size distributions after cloud evaporation. J. Appl. Meteorol. 34, 2649–2654. Bradbury, C., Bower, K.N., Choularton, T.W., Swietlicki, E., Birmili, W., Wiedensohler, A., Yuskiewicz, B.,
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